This document presents a semantic visualization and navigation approach for textual corpora. The approach aims to offer users three search modes: precise search, connotative search, and thematic search. It proposes new interaction paradigms to support the semantic aspects of the information space and guide users in their searches. The approach is based on semantic annotation of documents and represents information using a graph structure and fisheye visualization techniques. It allows navigation guided by a domain ontology for thematic searches or based on concept association relations for connotative searches. The goal is to help users locate relevant information and discover new knowledge.
HIGH-LEVEL SEMANTICS OF IMAGES IN WEB DOCUMENTS USING WEIGHTED TAGS AND STREN...IJCSEA Journal
The multimedia information retrieval from World Wide Web is a challenging issue. Describing multimedia object in general, images in particular with low-level features increases the semantic gap. From WWW, information present in a HTML document as textual keywords can be extracted for capturing semantic information with the view to narrow the semantic gap. The high-level textual information of images can be extracted and associated with the textual keywords, which narrow down the search space and improve the precision of retrieval. In this paper, a strength matrix is being proposed, which is based on the frequency of occurrence of keywords and the textual information pertaining to image URLs. The strength of these textual keywords are estimated and used for associating these keywords with the images present in the documents. The high-level semantics of the image is described in the HTML documents in the form of image name, ALT tag, optional description, etc., is used for estimating the strength. In addition, word position and weighting mechanism is also used for further improving the association textual keywords with the image related text. The effectiveness of information retrieval of the proposed technique is found to be comparatively better than many of the recently proposed retrieval techniques. The experimental results of the proposed method endorse the fact that image retrieval using image information and textual keywords is better than those of the text based and the content-based approaches.
Sentimental classification analysis of polarity multi-view textual data using...IJECEIAES
The data and information available in most community environments is complex in nature. Sentimental data resources may possibly consist of textual data collected from multiple information sources with different representations and usually handled by different analytical models. These types of data resource characteristics can form multi-view polarity textual data. However, knowledge creation from this type of sentimental textual data requires considerable analytical efforts and capabilities. In particular, data mining practices can provide exceptional results in handling textual data formats. Besides, in the case of the textual data exists as multi-view or unstructured data formats, the hybrid and integrated analysis efforts of text data mining algorithms are vital to get helpful results. The objective of this research is to enhance the knowledge discovery from sentimental multi-view textual data which can be considered as unstructured data format to classify the polarity information documents in the form of two different categories or types of useful information. A proposed framework with integrated data mining algorithms has been discussed in this paper, which is achieved through the application of X-means algorithm for clustering and HotSpot algorithm of association rules. The analysis results have shown improved accuracies of classifying the sentimental multi-view textual data into two categories through the application of the proposed framework on online polarity user-reviews dataset upon a given topics.
A Novel Approach for Travel Package Recommendation Using Probabilistic Matrix...IJSRD
This document proposes a novel approach for travel package recommendation using probabilistic matrix factorization (PMF). It discusses how existing recommendation systems are usually classification-based and supervised, whereas the proposed approach uses an unsupervised E-TRAST (Efficient-Tourist Relation Area Season Topic) model. The E-TRAST model represents travel packages and tourists using different topics modeled through PMF. It analyzes travel data characteristics and introduces a cocktail approach considering features like seasonal tourist performance to recommend customized travel packages.
A Domain Based Approach to Information Retrieval in Digital Libraries - Rotel...University of Bari (Italy)
The current abundance of electronic documents requires automatic techniques that support the users in understanding their content and extracting useful information. To this aim, improving the retrieval performance must necessarily go beyond simple lexical interpretation of the user queries, and pass through an understanding of their semantic content and aims. It goes without saying that any digital library would take enormous advantage from the availability of effective Information Retrieval techniques to provide to their users. This paper proposes an approach to Information Retrieval based on a correspondence of the domain of discourse between the query and the documents in the repository. Such an association is based on standard general-purpose linguistic resources (WordNet and WordNet Domains) and on a novel similarity assessment technique. Although the work is at a preliminary stage, interesting initial results suggest to go on extending and improving the approach.
Layout Based Information Retrieval from Document ImagesIOSR Journals
This document discusses layout-based information retrieval from document images. It proposes a system with three phases: 1) Intelligent layout analysis to extract layouts and edges from document images. 2) Representing layouts as tree structures for indexing and storage. 3) Logical layout analysis to identify meaningful elements like titles and text. It describes using white space analysis to segment layouts and properties to separate text and images. The system allows retrieving similar document images based on layout similarities. It also aims to analyze layouts logically to identify elements like titles and content lines for more meaningful information extraction from documents.
IRJET- Semantic Retrieval of Trademarks based on Text and Images Conceptu...IRJET Journal
The document proposes a novel Weakly-supervised Deep Matrix Factorization (WDMF) algorithm for social image tag refinement, assignment and retrieval. WDMF uncovers latent image and tag representations in a latent subspace by exploiting weakly supervised tagging information, visual structure and semantic structure. It can handle noisy, incomplete or subjective tags and noisy or redundant visual features. An optimization problem with a well-defined objective function is formulated and solved using gradient descent with curvilinear search. Extensive experiments on two real-world social image databases demonstrate the effectiveness of the approach.
This document provides a survey of semantic web personalization techniques. It begins by defining semantic web personalization and its advantages over traditional web personalization. It then classifies semantic web personalization approaches into several categories, including ontology-based, context-based, and hybrid recommendation systems. For each category, it provides examples of approaches and compares their methods and steps for personalization. The goal of the survey is to analyze and compare different techniques used for personalization in the semantic web.
Semantic Annotation Framework For Intelligent Information Retrieval Using KIM...dannyijwest
Due to the explosion of information/knowledge on the web and wide use of search engines for desired
information,the role of knowledge management(KM) is becoming more significant in an organization.
Knowledge Management in an Organization is used to create ,capture, store, share, retrieve and manage
information efficiently. The semantic web, an intelligent and meaningful web, tend to provide a promising
platform for knowledge management systems and vice versa, since they have the potential to give each
other the real substance for machine-understandable web resources which in turn will lead to an
intelligent, meaningful and efficient information retrieval on web. Today,the challenge for web community
is to integrate the distributed heterogeneous resources on web with an objective of an intelligent web
environment focusing on data semantics and user requirements. Semantic Annotation(SA) is being widely
used which is about assigning to the entities in the text and links to their semantic descriptions. Various
tools like KIM, Amaya etc may be used for semantic Annotation.
HIGH-LEVEL SEMANTICS OF IMAGES IN WEB DOCUMENTS USING WEIGHTED TAGS AND STREN...IJCSEA Journal
The multimedia information retrieval from World Wide Web is a challenging issue. Describing multimedia object in general, images in particular with low-level features increases the semantic gap. From WWW, information present in a HTML document as textual keywords can be extracted for capturing semantic information with the view to narrow the semantic gap. The high-level textual information of images can be extracted and associated with the textual keywords, which narrow down the search space and improve the precision of retrieval. In this paper, a strength matrix is being proposed, which is based on the frequency of occurrence of keywords and the textual information pertaining to image URLs. The strength of these textual keywords are estimated and used for associating these keywords with the images present in the documents. The high-level semantics of the image is described in the HTML documents in the form of image name, ALT tag, optional description, etc., is used for estimating the strength. In addition, word position and weighting mechanism is also used for further improving the association textual keywords with the image related text. The effectiveness of information retrieval of the proposed technique is found to be comparatively better than many of the recently proposed retrieval techniques. The experimental results of the proposed method endorse the fact that image retrieval using image information and textual keywords is better than those of the text based and the content-based approaches.
Sentimental classification analysis of polarity multi-view textual data using...IJECEIAES
The data and information available in most community environments is complex in nature. Sentimental data resources may possibly consist of textual data collected from multiple information sources with different representations and usually handled by different analytical models. These types of data resource characteristics can form multi-view polarity textual data. However, knowledge creation from this type of sentimental textual data requires considerable analytical efforts and capabilities. In particular, data mining practices can provide exceptional results in handling textual data formats. Besides, in the case of the textual data exists as multi-view or unstructured data formats, the hybrid and integrated analysis efforts of text data mining algorithms are vital to get helpful results. The objective of this research is to enhance the knowledge discovery from sentimental multi-view textual data which can be considered as unstructured data format to classify the polarity information documents in the form of two different categories or types of useful information. A proposed framework with integrated data mining algorithms has been discussed in this paper, which is achieved through the application of X-means algorithm for clustering and HotSpot algorithm of association rules. The analysis results have shown improved accuracies of classifying the sentimental multi-view textual data into two categories through the application of the proposed framework on online polarity user-reviews dataset upon a given topics.
A Novel Approach for Travel Package Recommendation Using Probabilistic Matrix...IJSRD
This document proposes a novel approach for travel package recommendation using probabilistic matrix factorization (PMF). It discusses how existing recommendation systems are usually classification-based and supervised, whereas the proposed approach uses an unsupervised E-TRAST (Efficient-Tourist Relation Area Season Topic) model. The E-TRAST model represents travel packages and tourists using different topics modeled through PMF. It analyzes travel data characteristics and introduces a cocktail approach considering features like seasonal tourist performance to recommend customized travel packages.
A Domain Based Approach to Information Retrieval in Digital Libraries - Rotel...University of Bari (Italy)
The current abundance of electronic documents requires automatic techniques that support the users in understanding their content and extracting useful information. To this aim, improving the retrieval performance must necessarily go beyond simple lexical interpretation of the user queries, and pass through an understanding of their semantic content and aims. It goes without saying that any digital library would take enormous advantage from the availability of effective Information Retrieval techniques to provide to their users. This paper proposes an approach to Information Retrieval based on a correspondence of the domain of discourse between the query and the documents in the repository. Such an association is based on standard general-purpose linguistic resources (WordNet and WordNet Domains) and on a novel similarity assessment technique. Although the work is at a preliminary stage, interesting initial results suggest to go on extending and improving the approach.
Layout Based Information Retrieval from Document ImagesIOSR Journals
This document discusses layout-based information retrieval from document images. It proposes a system with three phases: 1) Intelligent layout analysis to extract layouts and edges from document images. 2) Representing layouts as tree structures for indexing and storage. 3) Logical layout analysis to identify meaningful elements like titles and text. It describes using white space analysis to segment layouts and properties to separate text and images. The system allows retrieving similar document images based on layout similarities. It also aims to analyze layouts logically to identify elements like titles and content lines for more meaningful information extraction from documents.
IRJET- Semantic Retrieval of Trademarks based on Text and Images Conceptu...IRJET Journal
The document proposes a novel Weakly-supervised Deep Matrix Factorization (WDMF) algorithm for social image tag refinement, assignment and retrieval. WDMF uncovers latent image and tag representations in a latent subspace by exploiting weakly supervised tagging information, visual structure and semantic structure. It can handle noisy, incomplete or subjective tags and noisy or redundant visual features. An optimization problem with a well-defined objective function is formulated and solved using gradient descent with curvilinear search. Extensive experiments on two real-world social image databases demonstrate the effectiveness of the approach.
This document provides a survey of semantic web personalization techniques. It begins by defining semantic web personalization and its advantages over traditional web personalization. It then classifies semantic web personalization approaches into several categories, including ontology-based, context-based, and hybrid recommendation systems. For each category, it provides examples of approaches and compares their methods and steps for personalization. The goal of the survey is to analyze and compare different techniques used for personalization in the semantic web.
Semantic Annotation Framework For Intelligent Information Retrieval Using KIM...dannyijwest
Due to the explosion of information/knowledge on the web and wide use of search engines for desired
information,the role of knowledge management(KM) is becoming more significant in an organization.
Knowledge Management in an Organization is used to create ,capture, store, share, retrieve and manage
information efficiently. The semantic web, an intelligent and meaningful web, tend to provide a promising
platform for knowledge management systems and vice versa, since they have the potential to give each
other the real substance for machine-understandable web resources which in turn will lead to an
intelligent, meaningful and efficient information retrieval on web. Today,the challenge for web community
is to integrate the distributed heterogeneous resources on web with an objective of an intelligent web
environment focusing on data semantics and user requirements. Semantic Annotation(SA) is being widely
used which is about assigning to the entities in the text and links to their semantic descriptions. Various
tools like KIM, Amaya etc may be used for semantic Annotation.
INTELLIGENT SOCIAL NETWORKS MODEL BASED ON SEMANTIC TAG RANKINGdannyijwest
Social Networks has become one of the most popular platforms to allow users to communicate, and share their interests without being at the same geographical location. With the great and rapid growth of Social Media sites such as Facebook, LinkedIn, Twitter…etc. causes huge amount of user-generated content. Thus, the improvement in the information quality and integrity becomes a great challenge to all social media sites, which allows users to get the desired content or be linked to the best link relation using improved search / link technique. So introducing semantics to social networks will widen up the representation of the social networks. In this paper, a new model of social networks based on semantic tag ranking is introduced. This model is based on the concept of multi-agent systems. In this proposed model the representation of social links will be extended by the semantic relationships found in the vocabularies which are known as (tags) in most of social networks.The proposed model for the social media engine is based on enhanced Latent Dirichlet Allocation(E-LDA) as a semantic indexing algorithm, combined with Tag Rank as social network ranking algorithm. The improvements on (E-LDA) phase is done by optimizing (LDA) algorithm using the optimal parameters. Then a filter is introduced to enhance the final indexing output. In ranking phase, using Tag Rank based on the indexing phase has improved the output of the ranking. Simulation results of the proposed model have shown improvements in indexing and ranking output.
INFORMATION RETRIEVAL TECHNIQUE FOR WEB USING NLP ijnlc
This document presents a new approach for information retrieval from webpages using natural language processing (NLP). The proposed approach combines three techniques: 1) Vision-based Page Segmentation (VIPS), which creates a "vision tree" of visual blocks from a webpage's DOM tree based on visual cues; 2) Hierarchical Conditional Random Fields (HCRF), which labels HTML elements in the vision tree; and 3) Semi-Conditional Random Fields (Semi-CRF), which further segments text for more accurate results. These three techniques are integrated bidirectionally and run in parallel processing to retrieve entities from webpages more quickly and accurately than previous methods. The approach takes as input a text, entity, or URL and outputs the extracted
Survey of Machine Learning Techniques in Textual Document ClassificationIOSR Journals
Classification of Text Document points towards associating one or more predefined categories based
on the likelihood expressed by the training set of labeled documents. Many machine learning algorithms plays
an important role in training the system with predefined categories. The importance of Machine learning
approach has felt because of which the study has been taken up for text document classification based on the
statistical event models available. The aim of this paper is to present the important techniques and
methodologies that are employed for text documents classification, at the same time making awareness of some
of the interesting challenges that remain to be solved, focused mainly on text representation and machine
learning techniques.
Immune-Inspired Method for Selecting the Optimal Solution in Semantic Web Ser...IJwest
The increasing interest in developing efficient and effective optimization techniques has conducted researchers to turn their attention towards biology. It has been noticed that biology offers many clues for designing novel optimization techniques, these approaches exhibit self-organizing capabilities and permit the reachability of promising solutions without the existence of a central coordinator. In this paper we handle the problem of dynamic web service composition, by using the clonal selection algorithm. In order to assess the optimality rate of a given composition, we use the QOS attributes of the services involved in the workflow as well as, the semantic similarity between these components. The experimental evaluation shows that the proposed approach has a better performance in comparison with other approaches such as the genetic algorithm.
An Impact on Content Based Image Retrival A Perspective Viewijtsrd
The explosive increase and ubiquitous accessibility of visual data on the Web have led to the prosperity of research activity in image search or retrieval. With the ignorance of visual content as a ranking clue, methods with text search techniques for visual retrieval may suffer inconsistency between the text words and visual content. Content based image retrieval CBIR , which makes use of the representation of visual content to identify relevant images, has attracted sustained attention in recent two decades. Such a problem is challenging due to the intention gap and the semantic gap problems. Numerous techniques have been developed for content based image retrieval in the last decade. We conclude with several promising directions for future research. Shivanshu Jaiswal | Dr. Avinash Sharma ""An Impact on Content Based Image Retrival: A Perspective View"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020, URL: https://www.ijtsrd.com/papers/ijtsrd29969.pdf
Paper Url : https://www.ijtsrd.com/engineering/computer-engineering/29969/an-impact-on-content-based-image-retrival-a-perspective-view/shivanshu-jaiswal
MalayIK: An Ontological Approach to Knowledge Transformation in Malay Unstruc...IJECEIAES
The number of unstructured documents written in Malay language is enormously available on the web and intranets. However, unstructured documents cannot be queried in simple ways, hence the knowledge contained in such documents can neither be used by automatic systems nor could be understood easily and clearly by humans. This paper proposes a new approach to transform extracted knowledge in Malay unstructured document using ontology by identifying, organizing, and structuring the documents into an interrogative structured form. A Malay knowledge base, the MalayIK corpus is developed and used to test the MalayIK-Ontology against Ontos, an existing data extraction engine. The experimental results from MalayIKOntology have shown a significant improvement of knowledge extraction over Ontos implementation. This shows that clear knowledge organization and structuring concept is able to increase understanding, which leads to potential increase in sharable and reusable of concepts among the community.
UML MODELING AND SYSTEM ARCHITECTURE FOR AGENT BASED INFORMATION RETRIEVALijcsit
In this current technological era, there is an enormous increase in the information available on web and
also in the online databases. This information abundance increases the complexity of finding relevant
information. To solve such challenges, there is a need for improved and intelligent systems for efficient
search and retrieval. Intelligent Agents can be used for better search and information retrieval in a
document collection. The information required by a user is scattered in a large number of databases. In this
paper, the object oriented modeling for agent based information retrieval system is presented. The paper
also discusses the framework of agent architecture for obtaining the best combination terms that serve as
an input query to the information retrieval system. The communication and cooperation among the agents
are also explained. Each agent has a task to perform in information retrieval.
An Extensible Web Mining Framework for Real KnowledgeIJEACS
With the emergence of Web 2.0 applications that bestow rich user experience and convenience without time and geographical restrictions, web usage logs became a goldmine to researchers across the globe. User behavior analysis in different domains based on web logs has its utility for enterprises to have strategic decision making. Business growth of enterprises depends on customer-centric approaches that need to know the knowledge of customer behavior to succeed. The rationale behind this is that customers have alternatives and there is intense competition. Therefore business community needs business intelligence to have expert decisions besides focusing customer relationship management. Many researchers contributed towards this end. However, the need for a comprehensive framework that caters to the needs of businesses to ascertain real needs of web users. This paper presents a framework named eXtensible Web Usage Mining Framework (XWUMF) for discovering actionable knowledge from web log data. The framework employs a hybrid approach that exploits fuzzy clustering methods and methods for user behavior analysis. Moreover the framework is extensible as it can accommodate new algorithms for fuzzy clustering and user behavior analysis. We proposed an algorithm known as Sequential Web Usage Miner (SWUM) for efficient mining of web usage patterns from different data sets. We built a prototype application to validate our framework. Our empirical results revealed that the framework helps in discovering actionable knowledge.
1) The document discusses a review of semantic approaches for nearest neighbor search. It describes using an ontology to add a semantic layer to an information retrieval system to relate concepts using query words.
2) A technique called spatial inverted index is proposed to locate multidimensional information and handle nearest neighbor queries by finding the hospitals closest to a given address.
3) Several semantic approaches are described including using clustering measures, specificity measures, link analysis, and relation-based page ranking to improve search and interpret hidden concepts behind keywords.
A Survey on Knowledge Transfer between Knowledge-based SystemsTELKOMNIKA JOURNAL
The paper aims to clarify differences in knowledge sharing mechanisms between Knowledge-based Systems, including knowledge management system, web page-based knowledge, and expert system, in the hope that we can establish an automatic knowledge transfer between autonomous systems. This study lays the foundation for knowledge transfer mechanism where an autonomous Knowledge-based System may enhance its knowledge by using other system's knowledge. To design a knowledge transfer mechanism, the paper do a literature study by comparing three well-known protocols for knowledge sharing, OAI-PMH for knowledge management system, SPARQL for web page-based knowledge, and KQML for the expert system. The object of comparison is within three aspects, first is the ability to find another system, the second is knowledge retrieval from chosen system and third is how to add new knowledge into the system. The paper suggests that each protocol has its own strength and weakness, but when it comes to knowledge transfer, KQML covers more features. Therefore, based on this finding, the paper proposes a new model for autonomous knowledge transfer using KQML to enhance one Knowledge-based System's own knowledge.
Recommender systems have grown to be a critical research subject after the emergence of the first paper on collaborative filtering in the Nineties. Despite the fact that educational studies on recommender systems, has extended extensively over the last 10 years, there are deficiencies in the complete literature evaluation and classification of that research. Because of this, we reviewed articles on recommender structures, and then classified those based on sentiment analysis. The articles are categorized into three techniques of recommender system, i.e.; collaborative filtering (CF), content based and context based. We have tried to find out the research papers related to sentimental analysis based recommender system. To classify research done by authors in this field, we have shown different approaches of recommender system based on sentimental analysis with the help of tables. Our studies give statistics, approximately trends in recommender structures research, and gives practitioners and researchers with perception and destiny route on the recommender system using sentimental analysis. We hope that this paper enables all and sundry who is interested in recommender systems research with insight for destiny.
This document summarizes research posters being presented at a computer science and electrical engineering department research review. It describes 8 posters presented by BS, MS, and PhD students. The posters cover topics such as identifying political affiliations in blogs, statistically weighted visualization hierarchies, voter verifiable optical-scan voting, predictive caching in mobile networks, generating statistical volume models, predicting appropriate semantic web terms, approximating online social network community structure, and utilizing semantic policies for managing BGP route dissemination.
The document summarizes a research paper that proposes a customized ontological model for representing user profiles to improve web information gathering. The model uses both a global knowledge base and local user repositories to construct personalized ontologies. It introduces a multidimensional ontology mining method to analyze ontology concepts. The local repositories are then used to populate the personalized ontologies with background knowledge. An evaluation compares the proposed model to benchmarks and finds it successfully represents user profiles.
IRJET- Concept Extraction from Ambiguous Text Document using K-MeansIRJET Journal
This document discusses using a K-means clustering algorithm to extract concepts from ambiguous text documents. It involves preprocessing the text by tokenizing, removing stop words, and stemming words. The words are then represented as vectors and dimensionality reduction using PCA is applied. Finally, K-means clustering is used to group similar words into clusters to identify the overall concepts in the document without reading the entire text. The aim is to help users understand the key topics in a document in a time-efficient manner without having to read the full text.
RECURRENT FEATURE GROUPING AND CLASSIFICATION MODEL FOR ACTION MODEL PREDICTI...IJDKP
Content based retrieval has an advantage of higher prediction accuracy as compared to tagging based approach. However, the complexity in its representation and classification approach, results in lower processing accuracy and computation overhead. The correlative nature of the feature data are un-explored in the conventional modeling, where all the data features are taken as a set of feature values to give a decision. The recurrent feature class attribute is observed for the feature regrouping in action model prediction. In this paper a co-relative information, bounding grouping approach is suggested for action model prediction in CBMR application. The co-relative recurrent feature mapping results in faster retrieval process as compared to the conventional retrieval system.
Resource management and search is very important yet challenging in large-scale distributed systems like
P2Pnetworks. Most existing P2P systems rely on indexing to efficiently route queries over the network.
However, searches based on such indices face two key issues. First, majority of existing search schemes
often rely on simply keyword based indices that can only support exact string based matches without taking
into account the meaning of words. Second it is difficult, if not impossible, to devise query based indexing
schemes that can represent all possible concept combinations without resulting in exponential index sizes.
To address these problems, we present BSI, a novel P2P indexing and query routing strategy to support
semantic based content searches. The BSI indexing structure captures the semantic content of documents
using a reference ontology. Our indexing scheme can efficiently handle multi-concept queries by
maintaining summary level information for each individual concept and concept combinations using a
novel space-efficient Two-level Semantic Bloom Filter(TSBF) data structure. By using TSBFs to represent
a large document and query base, BSI significantly reduces the communication cost and storage cost of
indices. Furthermore, We devise a low-overhead mechanism to allow peers to dynamically estimate the
relevance strength of a peer for multi-concept queries with high accuracy solely based on TSBFs. We also
propose a routing index compression mechanism to observe peers’ dynamic storage limitations with
minimal loss of information by exploiting a reference ontology structure. Based on the proposed index
structure, we design a novel query routing algorithm that exploits semantic based information to route
queries to semantically relevant peers. Performance evaluation demonstrates that our proposed approach
can improve the search recall of unstructured P2P systems up to 383.71% while keeping the
communication cost at a low level compared to state-of-art search mechanism OSQR [7].
Detailed structure applicable to hybrid recommendation techniqueIAEME Publication
This document discusses a hybrid recommendation technique that combines content-based filtering, collaborative filtering, and demographic techniques to provide personalized point of interest (POI) recommendations for tourists. The technique uses a three-part process: 1) querying tourists for preferences and trip constraints, 2) using the tourist information to score POIs from each recommendation technique, and 3) clustering the top POIs to find the optimal trip area. The proposed hybrid approach aims to automatically select the most personalized POIs for tourists based on their initial information.
A survey on ontology based web personalizationeSAT Journals
Abstract Over the last decade the data on World Wide Web has been growing in an exponential manner. According to Google the data is accelerating with a speed of billion pages per day [24]. Internet has around 2 million users accessing the World Wide Web for various information [25].These numbers certainly raise a severe concern over information over load challenges for the users. Many researchers have been working to overcome the challenge with web personalization, many researchers are looking at ontology based web personalization as an answer to the information overload, as each individual is unique. In this paper we present an overview of ontology based web personalization, Challenges and a survey of the work. This paper also points future work in web personalization. Index Terms: Web Personalization, Ontology, User modeling, web usage mining.
This document summarizes research on ontology-based web personalization. It discusses how web personalization aims to personalize content based on a user's navigational behavior. Ontology-based approaches use formal domain knowledge to build more accurate user profiles than traditional web mining methods alone. The document surveys recent works applying ontologies to areas like user modeling, recommendation systems, and information retrieval. It also outlines challenges in developing personalized systems, such as building accurate user profiles and addressing privacy and scalability issues. Future work opportunities include better integrating ontology and web mining techniques to improve personalization over time as a user's interests evolve.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
USING ONTOLOGY BASED SEMANTIC ASSOCIATION RULE MINING IN LOCATION BASED SERVICESIJDKP
Recently, GPS and mobile devices allowed collecting a huge amount of mobility data. Researchers from
different communities have developed models and techniques for mobility analysis. But they mainly focused
on the geometric properties of trajectories and do not consider the semantic facet of moving objects. The
techniques are good at extracting patterns, but they are hard to interpret in a specific application domain.
This paper proposes a methodology to understand mobility data and semantically interpret trajectory
patterns. The process considers four different behavior types such as semantic, semantic and space,
semantic and time, and semantic and space-time. Finally, a system prototype was developed to evaluate the
behavior models in different aspects using one of the location based services. The results showed that
applying the semantic association rules could significantly reduce the number of available services and
customize the services based on the rules.
INTELLIGENT SOCIAL NETWORKS MODEL BASED ON SEMANTIC TAG RANKINGdannyijwest
Social Networks has become one of the most popular platforms to allow users to communicate, and share their interests without being at the same geographical location. With the great and rapid growth of Social Media sites such as Facebook, LinkedIn, Twitter…etc. causes huge amount of user-generated content. Thus, the improvement in the information quality and integrity becomes a great challenge to all social media sites, which allows users to get the desired content or be linked to the best link relation using improved search / link technique. So introducing semantics to social networks will widen up the representation of the social networks. In this paper, a new model of social networks based on semantic tag ranking is introduced. This model is based on the concept of multi-agent systems. In this proposed model the representation of social links will be extended by the semantic relationships found in the vocabularies which are known as (tags) in most of social networks.The proposed model for the social media engine is based on enhanced Latent Dirichlet Allocation(E-LDA) as a semantic indexing algorithm, combined with Tag Rank as social network ranking algorithm. The improvements on (E-LDA) phase is done by optimizing (LDA) algorithm using the optimal parameters. Then a filter is introduced to enhance the final indexing output. In ranking phase, using Tag Rank based on the indexing phase has improved the output of the ranking. Simulation results of the proposed model have shown improvements in indexing and ranking output.
INFORMATION RETRIEVAL TECHNIQUE FOR WEB USING NLP ijnlc
This document presents a new approach for information retrieval from webpages using natural language processing (NLP). The proposed approach combines three techniques: 1) Vision-based Page Segmentation (VIPS), which creates a "vision tree" of visual blocks from a webpage's DOM tree based on visual cues; 2) Hierarchical Conditional Random Fields (HCRF), which labels HTML elements in the vision tree; and 3) Semi-Conditional Random Fields (Semi-CRF), which further segments text for more accurate results. These three techniques are integrated bidirectionally and run in parallel processing to retrieve entities from webpages more quickly and accurately than previous methods. The approach takes as input a text, entity, or URL and outputs the extracted
Survey of Machine Learning Techniques in Textual Document ClassificationIOSR Journals
Classification of Text Document points towards associating one or more predefined categories based
on the likelihood expressed by the training set of labeled documents. Many machine learning algorithms plays
an important role in training the system with predefined categories. The importance of Machine learning
approach has felt because of which the study has been taken up for text document classification based on the
statistical event models available. The aim of this paper is to present the important techniques and
methodologies that are employed for text documents classification, at the same time making awareness of some
of the interesting challenges that remain to be solved, focused mainly on text representation and machine
learning techniques.
Immune-Inspired Method for Selecting the Optimal Solution in Semantic Web Ser...IJwest
The increasing interest in developing efficient and effective optimization techniques has conducted researchers to turn their attention towards biology. It has been noticed that biology offers many clues for designing novel optimization techniques, these approaches exhibit self-organizing capabilities and permit the reachability of promising solutions without the existence of a central coordinator. In this paper we handle the problem of dynamic web service composition, by using the clonal selection algorithm. In order to assess the optimality rate of a given composition, we use the QOS attributes of the services involved in the workflow as well as, the semantic similarity between these components. The experimental evaluation shows that the proposed approach has a better performance in comparison with other approaches such as the genetic algorithm.
An Impact on Content Based Image Retrival A Perspective Viewijtsrd
The explosive increase and ubiquitous accessibility of visual data on the Web have led to the prosperity of research activity in image search or retrieval. With the ignorance of visual content as a ranking clue, methods with text search techniques for visual retrieval may suffer inconsistency between the text words and visual content. Content based image retrieval CBIR , which makes use of the representation of visual content to identify relevant images, has attracted sustained attention in recent two decades. Such a problem is challenging due to the intention gap and the semantic gap problems. Numerous techniques have been developed for content based image retrieval in the last decade. We conclude with several promising directions for future research. Shivanshu Jaiswal | Dr. Avinash Sharma ""An Impact on Content Based Image Retrival: A Perspective View"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020, URL: https://www.ijtsrd.com/papers/ijtsrd29969.pdf
Paper Url : https://www.ijtsrd.com/engineering/computer-engineering/29969/an-impact-on-content-based-image-retrival-a-perspective-view/shivanshu-jaiswal
MalayIK: An Ontological Approach to Knowledge Transformation in Malay Unstruc...IJECEIAES
The number of unstructured documents written in Malay language is enormously available on the web and intranets. However, unstructured documents cannot be queried in simple ways, hence the knowledge contained in such documents can neither be used by automatic systems nor could be understood easily and clearly by humans. This paper proposes a new approach to transform extracted knowledge in Malay unstructured document using ontology by identifying, organizing, and structuring the documents into an interrogative structured form. A Malay knowledge base, the MalayIK corpus is developed and used to test the MalayIK-Ontology against Ontos, an existing data extraction engine. The experimental results from MalayIKOntology have shown a significant improvement of knowledge extraction over Ontos implementation. This shows that clear knowledge organization and structuring concept is able to increase understanding, which leads to potential increase in sharable and reusable of concepts among the community.
UML MODELING AND SYSTEM ARCHITECTURE FOR AGENT BASED INFORMATION RETRIEVALijcsit
In this current technological era, there is an enormous increase in the information available on web and
also in the online databases. This information abundance increases the complexity of finding relevant
information. To solve such challenges, there is a need for improved and intelligent systems for efficient
search and retrieval. Intelligent Agents can be used for better search and information retrieval in a
document collection. The information required by a user is scattered in a large number of databases. In this
paper, the object oriented modeling for agent based information retrieval system is presented. The paper
also discusses the framework of agent architecture for obtaining the best combination terms that serve as
an input query to the information retrieval system. The communication and cooperation among the agents
are also explained. Each agent has a task to perform in information retrieval.
An Extensible Web Mining Framework for Real KnowledgeIJEACS
With the emergence of Web 2.0 applications that bestow rich user experience and convenience without time and geographical restrictions, web usage logs became a goldmine to researchers across the globe. User behavior analysis in different domains based on web logs has its utility for enterprises to have strategic decision making. Business growth of enterprises depends on customer-centric approaches that need to know the knowledge of customer behavior to succeed. The rationale behind this is that customers have alternatives and there is intense competition. Therefore business community needs business intelligence to have expert decisions besides focusing customer relationship management. Many researchers contributed towards this end. However, the need for a comprehensive framework that caters to the needs of businesses to ascertain real needs of web users. This paper presents a framework named eXtensible Web Usage Mining Framework (XWUMF) for discovering actionable knowledge from web log data. The framework employs a hybrid approach that exploits fuzzy clustering methods and methods for user behavior analysis. Moreover the framework is extensible as it can accommodate new algorithms for fuzzy clustering and user behavior analysis. We proposed an algorithm known as Sequential Web Usage Miner (SWUM) for efficient mining of web usage patterns from different data sets. We built a prototype application to validate our framework. Our empirical results revealed that the framework helps in discovering actionable knowledge.
1) The document discusses a review of semantic approaches for nearest neighbor search. It describes using an ontology to add a semantic layer to an information retrieval system to relate concepts using query words.
2) A technique called spatial inverted index is proposed to locate multidimensional information and handle nearest neighbor queries by finding the hospitals closest to a given address.
3) Several semantic approaches are described including using clustering measures, specificity measures, link analysis, and relation-based page ranking to improve search and interpret hidden concepts behind keywords.
A Survey on Knowledge Transfer between Knowledge-based SystemsTELKOMNIKA JOURNAL
The paper aims to clarify differences in knowledge sharing mechanisms between Knowledge-based Systems, including knowledge management system, web page-based knowledge, and expert system, in the hope that we can establish an automatic knowledge transfer between autonomous systems. This study lays the foundation for knowledge transfer mechanism where an autonomous Knowledge-based System may enhance its knowledge by using other system's knowledge. To design a knowledge transfer mechanism, the paper do a literature study by comparing three well-known protocols for knowledge sharing, OAI-PMH for knowledge management system, SPARQL for web page-based knowledge, and KQML for the expert system. The object of comparison is within three aspects, first is the ability to find another system, the second is knowledge retrieval from chosen system and third is how to add new knowledge into the system. The paper suggests that each protocol has its own strength and weakness, but when it comes to knowledge transfer, KQML covers more features. Therefore, based on this finding, the paper proposes a new model for autonomous knowledge transfer using KQML to enhance one Knowledge-based System's own knowledge.
Recommender systems have grown to be a critical research subject after the emergence of the first paper on collaborative filtering in the Nineties. Despite the fact that educational studies on recommender systems, has extended extensively over the last 10 years, there are deficiencies in the complete literature evaluation and classification of that research. Because of this, we reviewed articles on recommender structures, and then classified those based on sentiment analysis. The articles are categorized into three techniques of recommender system, i.e.; collaborative filtering (CF), content based and context based. We have tried to find out the research papers related to sentimental analysis based recommender system. To classify research done by authors in this field, we have shown different approaches of recommender system based on sentimental analysis with the help of tables. Our studies give statistics, approximately trends in recommender structures research, and gives practitioners and researchers with perception and destiny route on the recommender system using sentimental analysis. We hope that this paper enables all and sundry who is interested in recommender systems research with insight for destiny.
This document summarizes research posters being presented at a computer science and electrical engineering department research review. It describes 8 posters presented by BS, MS, and PhD students. The posters cover topics such as identifying political affiliations in blogs, statistically weighted visualization hierarchies, voter verifiable optical-scan voting, predictive caching in mobile networks, generating statistical volume models, predicting appropriate semantic web terms, approximating online social network community structure, and utilizing semantic policies for managing BGP route dissemination.
The document summarizes a research paper that proposes a customized ontological model for representing user profiles to improve web information gathering. The model uses both a global knowledge base and local user repositories to construct personalized ontologies. It introduces a multidimensional ontology mining method to analyze ontology concepts. The local repositories are then used to populate the personalized ontologies with background knowledge. An evaluation compares the proposed model to benchmarks and finds it successfully represents user profiles.
IRJET- Concept Extraction from Ambiguous Text Document using K-MeansIRJET Journal
This document discusses using a K-means clustering algorithm to extract concepts from ambiguous text documents. It involves preprocessing the text by tokenizing, removing stop words, and stemming words. The words are then represented as vectors and dimensionality reduction using PCA is applied. Finally, K-means clustering is used to group similar words into clusters to identify the overall concepts in the document without reading the entire text. The aim is to help users understand the key topics in a document in a time-efficient manner without having to read the full text.
RECURRENT FEATURE GROUPING AND CLASSIFICATION MODEL FOR ACTION MODEL PREDICTI...IJDKP
Content based retrieval has an advantage of higher prediction accuracy as compared to tagging based approach. However, the complexity in its representation and classification approach, results in lower processing accuracy and computation overhead. The correlative nature of the feature data are un-explored in the conventional modeling, where all the data features are taken as a set of feature values to give a decision. The recurrent feature class attribute is observed for the feature regrouping in action model prediction. In this paper a co-relative information, bounding grouping approach is suggested for action model prediction in CBMR application. The co-relative recurrent feature mapping results in faster retrieval process as compared to the conventional retrieval system.
Resource management and search is very important yet challenging in large-scale distributed systems like
P2Pnetworks. Most existing P2P systems rely on indexing to efficiently route queries over the network.
However, searches based on such indices face two key issues. First, majority of existing search schemes
often rely on simply keyword based indices that can only support exact string based matches without taking
into account the meaning of words. Second it is difficult, if not impossible, to devise query based indexing
schemes that can represent all possible concept combinations without resulting in exponential index sizes.
To address these problems, we present BSI, a novel P2P indexing and query routing strategy to support
semantic based content searches. The BSI indexing structure captures the semantic content of documents
using a reference ontology. Our indexing scheme can efficiently handle multi-concept queries by
maintaining summary level information for each individual concept and concept combinations using a
novel space-efficient Two-level Semantic Bloom Filter(TSBF) data structure. By using TSBFs to represent
a large document and query base, BSI significantly reduces the communication cost and storage cost of
indices. Furthermore, We devise a low-overhead mechanism to allow peers to dynamically estimate the
relevance strength of a peer for multi-concept queries with high accuracy solely based on TSBFs. We also
propose a routing index compression mechanism to observe peers’ dynamic storage limitations with
minimal loss of information by exploiting a reference ontology structure. Based on the proposed index
structure, we design a novel query routing algorithm that exploits semantic based information to route
queries to semantically relevant peers. Performance evaluation demonstrates that our proposed approach
can improve the search recall of unstructured P2P systems up to 383.71% while keeping the
communication cost at a low level compared to state-of-art search mechanism OSQR [7].
Detailed structure applicable to hybrid recommendation techniqueIAEME Publication
This document discusses a hybrid recommendation technique that combines content-based filtering, collaborative filtering, and demographic techniques to provide personalized point of interest (POI) recommendations for tourists. The technique uses a three-part process: 1) querying tourists for preferences and trip constraints, 2) using the tourist information to score POIs from each recommendation technique, and 3) clustering the top POIs to find the optimal trip area. The proposed hybrid approach aims to automatically select the most personalized POIs for tourists based on their initial information.
A survey on ontology based web personalizationeSAT Journals
Abstract Over the last decade the data on World Wide Web has been growing in an exponential manner. According to Google the data is accelerating with a speed of billion pages per day [24]. Internet has around 2 million users accessing the World Wide Web for various information [25].These numbers certainly raise a severe concern over information over load challenges for the users. Many researchers have been working to overcome the challenge with web personalization, many researchers are looking at ontology based web personalization as an answer to the information overload, as each individual is unique. In this paper we present an overview of ontology based web personalization, Challenges and a survey of the work. This paper also points future work in web personalization. Index Terms: Web Personalization, Ontology, User modeling, web usage mining.
This document summarizes research on ontology-based web personalization. It discusses how web personalization aims to personalize content based on a user's navigational behavior. Ontology-based approaches use formal domain knowledge to build more accurate user profiles than traditional web mining methods alone. The document surveys recent works applying ontologies to areas like user modeling, recommendation systems, and information retrieval. It also outlines challenges in developing personalized systems, such as building accurate user profiles and addressing privacy and scalability issues. Future work opportunities include better integrating ontology and web mining techniques to improve personalization over time as a user's interests evolve.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
USING ONTOLOGY BASED SEMANTIC ASSOCIATION RULE MINING IN LOCATION BASED SERVICESIJDKP
Recently, GPS and mobile devices allowed collecting a huge amount of mobility data. Researchers from
different communities have developed models and techniques for mobility analysis. But they mainly focused
on the geometric properties of trajectories and do not consider the semantic facet of moving objects. The
techniques are good at extracting patterns, but they are hard to interpret in a specific application domain.
This paper proposes a methodology to understand mobility data and semantically interpret trajectory
patterns. The process considers four different behavior types such as semantic, semantic and space,
semantic and time, and semantic and space-time. Finally, a system prototype was developed to evaluate the
behavior models in different aspects using one of the location based services. The results showed that
applying the semantic association rules could significantly reduce the number of available services and
customize the services based on the rules.
The document discusses a review process for analyzing contextual human information behavior factors in web usage mining. It first searches journals and search engines to find empirical studies related to gender differences, prior knowledge and cognitive styles. These studies are then examined to analyze how these three human factors impact web-based interactions. While some commercial analysis applications exist, more work still needs to be done by researchers and developers to build efficient and powerful tools for studying human information behavior.
INTELLIGENT INFORMATION RETRIEVAL WITHIN DIGITAL LIBRARY USING DOMAIN ONTOLOGYcscpconf
A digital library is a type of information retrieval (IR) system. The existing information retrieval
methodologies generally have problems on keyword-searching. We proposed a model to solve
the problem by using concept-based approach (ontology) and metadata case base. This model
consists of identifying domain concepts in user’s query and applying expansion to them. The
system aims at contributing to an improved relevance of results retrieved from digital libraries
by proposing a conceptual query expansion for intelligent concept-based retrieval. We need to
import the concept of ontology, making use of its advantage of abundant semantics and
standard concept. Domain specific ontology can be used to improve information retrieval from
traditional level based on keyword to the lay based on knowledge (or concept) and change the
process of retrieval from traditional keyword matching to semantics matching. One approach is
query expansion techniques using domain ontology and the other would be introducing a case
based similarity measure for metadata information retrieval using Case Based Reasoning
(CBR) approach. Results show improvements over classic method, query expansion using
general purpose ontology and a number of other approaches.
Research Inventy : International Journal of Engineering and Scienceresearchinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
The document describes a proposed fuzzy logic-based model for classifying web users in a personalized search system. The model collects user browsing data using a customized browser. It then fuzzifies the data and generates fuzzy rules using decision trees. These rules are used to label search pages and group users according to their search interests. The model is evaluated against a Bayesian classifier and shown to perform better. The goal is to handle the dynamic and fluctuating nature of user behavior and interests that exist in a personalized web search environment.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
User-Centred Design to Support Exploration and Path Creation in Cultural Her...pathsproject
This document describes research on developing a prototype system to enhance user interaction with cultural heritage collections through a pathway metaphor. It involved gathering user requirements through surveys and interviews. Key findings include:
1) Existing online paths tend to be linear and static, limiting exploration, though users preferred more flexible, theme-based paths that allowed branching.
2) Interviews found the path metaphor could represent search histories, journeys of discovery, linked metadata, guides into collections, routes through collections, and more.
3) An interaction model was developed involving consuming, collecting, creating and communicating about paths to support exploration, learning and engagement.
4) The prototype aims to integrate path creation, use and sharing to better support
Here are the key points about using content-based filtering techniques:
- Content-based filtering relies on analyzing the content or description of items to recommend items similar to what the user has liked in the past. It looks for patterns and regularities in item attributes/descriptions to distinguish highly rated items.
- The item content/descriptions are analyzed automatically by extracting information from sources like web pages, or entered manually from product databases.
- It focuses on objective attributes about items that can be extracted algorithmically, like text analysis of documents.
- However, personal preferences and what makes an item appealing are often subjective qualities not easily extracted algorithmically, like writing style or taste.
- So while content-based filtering can
A Multimodal Approach to Incremental User Profile Building dannyijwest
In the navigational applications, radar and satellite requires a device that is a radar altimeter. The working frequency of this system is 4.2 to 4.3GHz and also requires less weight, low profile, and high gain antennas. The above mentioned application is possible with microstrip antenna as also known as planar antenna. In this paper, the microstrip antennas are designed at 4.3GHz (C-band) in rectangular and circular shape patch antennas in single element and arrays with parasitic elements placed in H-plane coupling. The performance of all these shapes is analyzed in terms of radiation pattern, half power points, and gain and impedance bandwidth in MATLAB. This work extended here with designed in different shapes like Rhombic, Pentagon, Octagon and Edges-12 etc. Further these parameters are simulated in ANSOFT- HFSSTM V9.0 simulator.
This is the presentation of the Juan Cruz-Benito’s PhD “On data-driven systems analyzing, supporting and enhancing users’ interaction and experience” that was defended on September 3rd, 2018 in the Faculty of Sciences at University of Salamanca Spain. This PhD was graded with the maximum qualification “Sobresaliente Cum Laude”.
Comparative Analysis of Collaborative Filtering TechniqueIOSR Journals
The document compares different collaborative filtering techniques for making recommendations. It finds that hybrid collaborative filtering, which combines memory-based, model-based and other techniques, generally performs better than memory-based or model-based alone in terms of scalability, accuracy and memory consumption. It also proposes adding a normalization step to traditional collaborative filtering to improve accuracy by addressing the uneven distribution of ratings across items.
Efficient Way to Identify User Aware Rare Sequential Patterns in Document Str...ijtsrd
The document proposes a method to identify rare sequential topic patterns in document streams that are uncommon overall but relatively frequent for specific users. It involves three phases: pre-processing to extract topics and identify user sessions, generating all sequential topic pattern candidates and their expected support values for each user, and selecting rare patterns by analyzing rarity from a user-aware perspective. Experiments on real and synthetic datasets show the approach can effectively discover meaningful rare patterns that reflect user characteristics.
This document discusses a navigation cost modeling technique based on ontology for effective navigation of query results from large datasets. It presents an approach that uses concept hierarchies built from annotated data to categorize results and reduce the navigation cost for users. An initial navigation tree is constructed from the dataset ontology and refined by removing empty nodes. The tree is then dynamically expanded at certain points to minimize the user's navigation cost and quickly reach the desired results.
Navigation Cost Modeling Based On OntologyIOSR Journals
This document discusses a navigation cost modeling technique based on ontology for effective navigation of query results from large datasets. It presents an approach that uses concept hierarchies built from annotated data to categorize results and reduce the number displayed to users. An initial navigation tree is constructed from the concept hierarchies and optimized by removing empty nodes. EdgeCuts are then used to expand portions of the tree to minimize navigation cost for users. The proposed technique aims to provide more efficient navigation of query results than existing systems through categorization, ranking and modeling of navigation costs.
Recommender systems: a novel approach based on singular value decompositionIJECEIAES
Due to modern information and communication technologies (ICT), it is increasingly easier to exchange data and have new services available through the internet. However, the amount of data and services available increases the difficulty of finding what one needs. In this context, recommender systems represent the most promising solutions to overcome the problem of the so-called information overload, analyzing users' needs and preferences. Recommender systems (RS) are applied in different sectors with the same goal: to help people make choices based on an analysis of their behavior or users' similar characteristics or interests. This work presents a different approach for predicting ratings within the model-based collaborative filtering, which exploits singular value factorization. In particular, rating forecasts were generated through the characteristics related to users and items without the support of available ratings. The proposed method is evaluated through the MovieLens100K dataset performing an accuracy of 0.766 and 0.951 in terms of mean absolute error and root-mean-square error.
1. The document proposes techniques to improve search performance by matching schemas between structured and unstructured data sources.
2. It involves constructing schema mappings using named entities and schema structures. It also uses strategies to narrow the search space to relevant documents.
3. The techniques were shown to improve search accuracy and reduce time/space complexity compared to existing methods.
Similar to SEMANTIC VISUALIZATION AND NAVIGATION IN TEXTUAL CORPUS (20)
Online Paper Submission - International Journal of Information Sciences and T...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
Call for Papers - 5th International Conference on Cloud, Big Data and IoT (CB...ijistjournal
5th International Conference on Cloud, Big Data and IoT (CBIoT 2024) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Cloud, Big Data and IoT.
PERFORMANCE ANALYSIS OF PARALLEL IMPLEMENTATION OF ADVANCED ENCRYPTION STANDA...ijistjournal
Cryptography is the study of mathematical techniques related to aspects of information security such as confidentiality, data integrity, entity authentication, and data origin authentication. Most cryptographic algorithms function more efficiently when implemented in hardware than in software running on single processor. However, systems that use hardware implementations have significant drawbacks: they are unable to respond to flaws discovered in the implemented algorithm or to changes in standards. As an alternative, it is possible to implement cryptographic algorithms in software running on multiple processors. However, most of the cryptographic algorithms like DES (Data Encryption Standard) or 3DES have some drawbacks when implemented in software: DES is no longer secure as computers get more powerful while 3DES is relatively sluggish in software. AES (Advanced Encryption Standard), which is rapidly being adopted worldwide, provides a better combination of performance and enhanced network security than DES or 3DES by being computationally more efficient than these earlier standards. Furthermore, by supporting large key sizes of 128, 192, and 256 bits, AES offers higher security against brute-force attacks.
In this paper, AES has been implemented with single processor. Then the result has been compared with parallel implementations of AES with 2 varying different parameters such as key size, number of rounds and extended key size, and show how parallel implementation of the AES offers better performance yet flexible enough for cryptographic algorithms.
Submit Your Research Articles - International Journal of Information Sciences...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
INFORMATION THEORY BASED ANALYSIS FOR UNDERSTANDING THE REGULATION OF HLA GEN...ijistjournal
Considering information entropy (IE), HLA surface expression (SE) regulation phenomenon is considered as information propagation channel with an amount of distortion. HLA gene SE is considered as sink regulated by the inducible transcription factors (TFs) (source). Previous work with a certain number of bin size, IEs for source and receiver is computed and computation of mutual information characterizes the dependencies of HLA gene SE on some certain TFs in different cells types of hematopoietic system under the condition of leukemia. Though in recent time information theory is utilized for different biological knowledge generation and different rules are available in those specific domains of biomedical areas; however, no such attempt is made regarding gene expression regulation, hence no such rule is available. In this work, IE calculation with varying bin size considering the number of bins is approximately half of the sample size of an attribute also confirms the previous inferences.
Call for Research Articles - 5th International Conference on Artificial Intel...ijistjournal
5th International Conference on Artificial Intelligence and Machine Learning (CAIML 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and Machine Learning. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Machine Learning in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Computer Science, Engineering and Applications.
Online Paper Submission - International Journal of Information Sciences and T...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
SYSTEM IDENTIFICATION AND MODELING FOR INTERACTING AND NON-INTERACTING TANK S...ijistjournal
System identification from the experimental data plays a vital role for model based controller design. Derivation of process model from first principles is often difficult due to its complexity. The first stage in the development of any control and monitoring system is the identification and modeling of the system. Each model is developed within the context of a specific control problem. Thus, the need for a general system identification framework is warranted. The proposed framework should be able to adapt and emphasize different properties based on the control objective and the nature of the behavior of the system. Therefore, system identification has been a valuable tool in identifying the model of the system based on the input and output data for the design of the controller. The present work is concerned with the identification of transfer function models using statistical model identification, process reaction curve method, ARX model, genetic algorithm and modeling using neural network and fuzzy logic for interacting and non interacting tank process. The identification technique and modeling used is prone to parameter change & disturbance. The proposed methods are used for identifying the mathematical model and intelligent model of interacting and non interacting process from the real time experimental data.
Call for Research Articles - 4th International Conference on NLP & Data Minin...ijistjournal
4th International Conference on NLP & Data Mining (NLDM 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and Data Mining.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.
Research Article Submission - International Journal of Information Sciences a...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
Call for Papers - International Journal of Information Sciences and Technique...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
Implementation of Radon Transformation for Electrical Impedance Tomography (EIT)ijistjournal
Radon Transformation is generally used to construct optical image (like CT image) from the projection data in biomedical imaging. In this paper, the concept of Radon Transformation is implemented to reconstruct Electrical Impedance Topographic Image (conductivity or resistivity distribution) of a circular subject. A parallel resistance model of a subject is proposed for Electrical Impedance Topography(EIT) or Magnetic Induction Tomography(MIT). A circular subject with embedded circular objects is segmented into equal width slices from different angles. For each angle, Conductance and Conductivity of each slice is calculated and stored in an array. A back projection method is used to generate a two-dimensional image from one-dimensional projections. As a back projection method, Inverse Radon Transformation is applied on the calculated conductance and conductivity to reconstruct two dimensional images. These images are compared to the target image. In the time of image reconstruction, different filters are used and these images are compared with each other and target image.
Online Paper Submission - 6th International Conference on Machine Learning & ...ijistjournal
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.
Submit Your Research Articles - International Journal of Information Sciences...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
BER Performance of MPSK and MQAM in 2x2 Almouti MIMO Systemsijistjournal
Almouti published the error performance of the 2x2 space-time transmit diversity scheme using BPSK. One of the key techniques employed for correcting such errors is the Quadrature amplitude modulation (QAM) because of its efficiency in power and bandwidth.. In this paper we explore the error performance of the 2x2 MIMO system using the Almouti space-time codes for higher order PSK and M-ary QAM. MATLAB was used to simulate the system; assuming slow fading Rayleigh channel and additive white Gaussian noise. The simulated performance curves were compared and evaluated with theoretical curves obtained using BER tool on the MATLAB by setting parameters for random generators. The results shows that the technique used do find a place in correcting error rates of QAM system of higher modulation schemes. The model can equally be used not only for the criteria of adaptive modulation but for a platform to design other modulation systems as well.
Online Paper Submission - International Journal of Information Sciences and T...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
Call for Papers - International Journal of Information Sciences and Technique...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
International Journal of Information Sciences and Techniques (IJIST)ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
BRAIN TUMOR MRIIMAGE CLASSIFICATION WITH FEATURE SELECTION AND EXTRACTION USI...ijistjournal
Feature extraction is a method of capturing visual content of an image. The feature extraction is the process to represent raw image in its reduced form to facilitate decision making such as pattern classification. We have tried to address the problem of classification MRI brain images by creating a robust and more accurate classifier which can act as an expert assistant to medical practitioners. The objective of this paper is to present a novel method of feature selection and extraction. This approach combines the Intensity, Texture, shape based features and classifies the tumor as white matter, Gray matter, CSF, abnormal and normal area. The experiment is performed on 140 tumor contained brain MR images from the Internet Brain Segmentation Repository. The proposed technique has been carried out over a larger database as compare to any previous work and is more robust and effective. PCA and Linear Discriminant Analysis (LDA) were applied on the training sets. The Support Vector Machine (SVM) classifier served as a comparison of nonlinear techniques Vs linear ones. PCA and LDA methods are used to reduce the number of features used. The feature selection using the proposed technique is more beneficial as it analyses the data according to grouping class variable and gives reduced feature set with high classification accuracy.
Research Article Submission - International Journal of Information Sciences a...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
SEMANTIC VISUALIZATION AND NAVIGATION IN TEXTUAL CORPUS
1. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.1, January 2012
DOI : 10.5121/ijist.2012.2105 53
SEMANTIC VISUALIZATION AND NAVIGATION IN
TEXTUAL CORPUS
Férihane Kboubi, Anja Habacha Chaibi and Mohamed BenAhmed
RIADI-ENSI, University Campus of Manouba
2010, Manouba, Tunisie
Ferihane.Kboubi@riadi.rnu.tn, Anja.Habacha@ensi.rnu.tn,
Mohamed.benAhmed@riadi.rnu.tn
ABSTRACT
This paper gives a survey of related work on the information visualization domain and study the real
integration of the cartography paradigms in actual information search systems. Based on this study, we
propose a semantic visualization and navigation approach which offer to users three search modes: precise
search, connotative search and thematic search. The objective is to propose to the users of an information
search system, new interaction paradigms which support the semantic aspect of the considered information
space and guide users in their searches by assisting them to locate their interest center and to improve
serendipity.
KEYWORDS
Information visualization, semantic navigation, cartography paradigms, connotative search, thematic
search
1. INTRODUCTION
Available information on Internet grows at an exponential rate. Data in these information systems
is becoming more complex and more dynamic. As users with different backgrounds, traits,
abilities, dispositions, and intentions increase dramatically, users’ needs also become more
diverse and complicated. Therefore the demand for a more effective and efficient means for
managing and exploring data became a pressing issue. This poses a challenge to the traditional
approaches and techniques used in current information retrieval systems. These systems use a
keyword-based search process which is discontinuous because users have no control over the
internal matching process which is not transparent to users. Besides, the output of search systems
as result list presentation is linear and has a limited display capacity. Relationships and
connections among documents are rarely illustrated. The retrieval environment lacks an
interactive mechanism for users to browse. These inherent weaknesses of traditional information
retrieval systems prevent them from coping with the sheer complexity of information needs and
the multitude of data dimensionality.
The query-based search engines support only one search type “the precise search” which
supposes that user know exactly for what they look for: a precise paper knowing its title, authors
and major theme). It is not unusual for users to input search terms that are different from index
2. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.1, January 2012
54
terms used by the system. It will be very interesting to offer to users other search type such as
“thematic search” (allowing users to navigate in the corpus according to a particular theme),
“connotative search” (allowing users to discover the associated and similar concepts of their
interest concepts) or “exploratory search” (allowing users to make an idea about the content of
the corpus; and after a preliminary consultation that they will exactly define their needs).
As regards to the visualization methods, the study carried out by [1] showed that the result lists
return an enormous quantity of information. This leads to a cognitive overload for users who
cannot, in the majority of the cases, consult all the returned documents.
An innovative idea to guide users in their searches is to provide them an interaction method
allowing them locating their needs throw the navigation in the document informational space.
This type of interaction benefits from an important characteristic of the human cognition: it is
easier to the users to discover or to locate for what they look, than to produce formal descriptions
of information which they do not have. So, navigation within maps can replace advantageously
writing of queries as far as semantics, being more explicit in maps, limits the problems of
confusion and ambiguity often met in the query-based systems. Based on this innovative idea, the
goal of this work is to find and propose solutions for these evocated problems.
The remaining of this paper is organized as following. In section 2, we present a survey of
existing semantic cartography paradigms and discuss about their incorporation on information
retrieval process. In section 3, we describe our semantic visualization approach which supports
three search types: precise search, thematic search and connotative search. In this section we
present two navigation approaches. The first one is based on domain ontology and the second is
based on association relations.
2. SEMANTIC CARTOGRAPHY
Information retrieval visualization refers to a process that transforms the invisible abstract data
and their semantic relationships in a data collection into a visible display and visualizes the
internal retrieval processes for users. Basically, information retrieval visualization is comprised of
two components: visual information presentation and visual information retrieval.
According to Card [2] and Tricot [3] there are three visual information presentation paradigms
(which they called also cartography paradigms):
− The representation paradigms. They allow representing the structure of information. We
distinguish between five types of information structures which are: the tabular structure [4],
the treelike structure [5], the graph structure (Hypergraph [23] and TouchGraph systems),
the temporal structure (ThemeRiver [6], spiral representation [7]) and the agglomerative
structure (Themescapes [8]).
− The visualization paradigms. They represent the means of displaying information
representations in a clear and coherent way on a limited space so that a person can become
aware quickly of the presented information. Visualization techniques are classified in two
groups: uniform visualization techniques (overview+details [9]) and the not uniform
visualization techniques (document lens [10], the elusive walls [11], fisheye [12]).
− The interaction paradigms. They concern techniques allowing users to interact with the
produced visualizations like: zoom and pan, focus and context, dynamic filtering [13],
semantic zoom [14][15].
3. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.1, January 2012
55
The visual information presentation provides a platform where visual information retrieval is
performed or conducted. According to Zhang there are three information retrieval visualization
paradigms [16]:
− The QB paradigm (Query searching and Browsing). Initially a query is required to
limit the set of search results. Then a visualization of these results is constructed in
which users may browse to concentrate their visual space for more specific
information.
− The BQ paradigm (Browsing and Query searching). A visual presentation of the
information set is first established for browsing. Then users submit their search
queries to the visualization environment and corresponding search results are
highlighted or presented within the visual presentation contexts.
− The BO paradigm (Browsing Only). This paradigm does not integrate any query
searching components.
For a more detailed survey on semantic cartography paradigms see [17]. In spite of the variety of
cartography paradigms proposed in the literature, their concrete integration on web remains
however very limited and this for two main considerations. In the first place, from the user point
of view, numerous are the ones who are not familiarized yet with these new paradigms. Secondly,
as regards to material and software configurations, a big part of equipments connected on the net
are not adapted to this type of applications.
Nevertheless, the evolution of hardware performance and the considerable development in the
domain of interactive information visualization for years, allowed the emergence of new systems
integrating information visualization techniques with varied levels, such as: Kartoo
(http://www.kartoo.com), Toolnet (http://www.toolenet.com), Ujiko (http://www.Ujiko.com) and
ArnetMiner (http://www.arnetminer.org).
All these systems are based on query definition as a search mode and they offer to users a
graphical result maps as output. However, interaction means given to users remain elementary
(selection, zoom). There are no means of semantic interaction and navigation in the informational
space.
Based only on a query search mode, these systems support only a single search type which is the
precise search (where users know exactly for what they look for). It would be very useful to
propose to users other search mode guiding and assisting them in their searches and allowing
them to navigate in the produced maps to refine their searches and to discover new knowledge.
3. OUR SEMANTIC MULTIFACET NAVIGATION APPROACH
The principal idea of this work is to propose a model allowing to put in evidence semantic
inherent to the textual corpus. Our model is based on the result of the semantic annotation and
indexation of textual documents [18][19][20]; and represents a new model of graphic
visualization and semantic navigation (Figure 1).
The annotation process generates three types of annotations: descriptive annotations, conceptual
annotations and thematic annotations.
4. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.1, January 2012
56
− The descriptive annotations are relative to: bibliographic annotations (title, authors,
publication date), content descriptors (author abstract and key-words), technical annotations
(format, size).
− The conceptual annotations are relative to the concepts evoked in the document, their
respective pertinence degree, and their respective association relations.
− The thematic annotations are relative to the major theme and the set of minor themes
handled in the document, and to the thematic association relations.
Our information representation and visualization model is based on the cartography paradigms
studied in the state of the art. The aim is to reduce the cognitive effort of readers as regards to the
classical result list representation mode. Indeed, graphical visualizations allow putting in
evidence the pertinent information for users. According to Gershon and Page [21] the
visualization amplifies the cognition and it allows to users and readers to observe, to understand
and to make sense of these information.
Figure 1. General principle of our explorative and thematic search approach
For representing and visualizing the information, we used a graph shaped representation based on
the fisheye visualization techniques. This type of representation is adequate for representing
semantic relations in the annotated domain ontology and the association networks (hierarchical
relations between the concepts, the association relation between the concepts, the similarity
relations between the documents, etc.). The fisheye technique allows putting in evidence the
interest center of the user when he navigates in the graph.
5. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.1, January 2012
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In order to experiment our interactive visualization scenarios, we used the hypergraph-0.6.3
applet1
since it is based on graph representation and fisheye visualization paradigms.
Our new interaction mode offers to users a multi-approach of semantic navigation:
− Domain ontology based navigation approach allowing users to make thematic searches to
explore document informational space according to their themes of interest.
− Concept association based navigation approach allowing the users to make connotative
searches by navigating in the conceptual association graphs.
− Similarity relation based navigation approach allowing users to make another type of
connotative searches by navigating in the document similarity relation graphs.
3.1. Navigation guided by the domain ontology
The idea is to visualize the semantic content of the textual document corpus through a graphic
representation of the annotated domain ontology. Initially the domain ontology is visualized as a
hierarchy of themes and concepts, in which a user can navigate from one theme to another and
from one concept to another in order to localize his interest center (Figure 2). For a given
concept, the user can ask to display the titles of all documents indexed by this concept and to
order them by their pertinence degree. The user can afterward consult the description of a
document of his choice. This description represents a semantic summary of the selected document
and contains descriptive, conceptual and thematic annotations already extracted during the
annotation step.
Several advantages ensue from this navigation approach. Effectively, this navigation approach
offers a thematic search mode by reflecting for a given domain the semantic common to the
majority of users. It offers to users a representation of knowledge close to the cognitive model
which they have on the domain, what avoids them getting lost in the semantic map and allows
them to localize quickly their interest center.
Nielsen [22] came up with three fundamental questions that the users (Internet surfers) face when
they navigate the cyberspace: where am I now?, where have I been?, and where can I go next?.
This navigation approach helps users answer these questions and minimize the problems of lost in
information space and disorientation syndrome.
1
Available on line at http://hypergraph.sourceforge.net/
6. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.1, January 2012
58
Figure 2. Navigation guided by the domain ontology (1) overview of the general themes, (2)
graphic representation of the concept hierarchy of the selected theme, (3) visualization of the
document indexed by the selected concept with their respective degree of pertinence, (4)
visualization of the semantic annotation summary of the selected document
The visualization example, presented by Figure 3, illustrates the navigation path which a user can
make to access to documents indexed by the concepts “Multi-agent System”. The Figure 3.a
corresponds to a view of the domain ontology representation centered on three themes: security,
artificial intelligence and information system.
In this arborescence the user navigates to localize his interest center. In this example, the user
chooses initially the theme “Artificial Intelligence”, then he chooses the subtheme “Application
and expert systems”. After consulting the map the user selects the concept “Multi-Agent System”.
A view containing titles and relevance degrees of documents annotated by this concept is shown
allowing the user to make a global idea about the documents indexed by this concept and their
respective pertinence (Figure 3.b). The user can display a detailed description of every document
before downloading it or visualizing it in the full text.
Figure 4 illustrates an example of a document description selected by a user. The document
description corresponds to the descriptive annotations, the key concepts, the cooccurrence
hypergraph and the thematic composition of the document (major theme, minor themes). This
figure shows that the document deals with three themes: mainly “Artificial Intelligence: And
Expert Systems application” who is considered as the major theme and “Security: Cryptography”
and “Security: Network Security” who are considered as minor themes.
7. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.1, January 2012
59
(a)
(b)
Figure 3. Example of navigation path
3.2. Association relation based navigation
When navigating in the domain ontology, the user can focus his attention on a concept and wishes
to know what are the concepts associated to it (Figure 5). The analysis of the conceptual
association relations in the corpus allows answering this kind of needs. Our idea is to build for
every concept an association graph allowing users to discover the association relations of their
interest concept and to visualize documents relative to an association of their choice. For the
identification of the conceptual association graphs we are based on the construction and the
analysis of the cooccurrence networks [18].
8. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.1, January 2012
60
Figure 4. Example of document selected in the first path
So, for every concept of the ontology we determine the set of the concepts with which it is
associated by a cooccurrence relation. We measure the degree of association of every relation
according to the number of documents in which both concepts collocate. The analysis of the
cooccurrence relations between concepts allows to index documents by conceptual associations.
Figure 5. Association Relation based Navigation (1) graphic representation of the domain
ontology, (2) visualization of the association relations of the selected concept, (3) visualization of
the documents indexed by the selected association relation, (4) visualization of the semantic
annotation summary of the selected document
Figure 6 shows an example of concept association hypergraph concerning the concept “Multi-
Agent System”. The central node represents the concept of interest. The first level of nodes
represents the set of concepts associated to the central concept. The label of an edge between the
central concept and another concept represents the association degree between the two concepts.
From this figure, we can note for example that the concept “Multi-Agent System” is associated
with the concept “Semantic Network” with an association degree equal to 0.36 and to the concept
“Authentication” with an association degree equal to 0.13.
9. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.1, January 2012
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The second level of nodes represents documents indexed by these conceptual associations. The
label of an edge which connects a document node and an associated concept node represents the
relevance degree of the document with regard to both concepts (associated concept and central
concept). For example, Figure 6.b shows that three documents are indexed by the association
relation between the two concepts “Multi-Agent System” and “Authentication”. The first
document entitled “A security solution for mobile agents” has a relevance degree equal to 0.642.
The second document entitled “Securing Mobile Agents” has a relevance degree equal to 0.682.
The third document entitled “Securing Mobile Agents by cloning them” has a relevance degree
equal to 0.645.
The main interest of integrating conceptual association relations in the visualization process is to
allow users to discover information related to their initial interest center what contributes to
enlarge their domain knowledge. Besides, the visualization of association relations allows
reflecting the real context in which concepts are evoked in documents. So users could refine their
search according to the conceptual associations which are relevant to them (filter documents) and
to discover new knowledge.
(a)
(b)
Figure 6. Navigation in the association Hypergraphe of the concept « Multi-Agent System »
10. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.1, January 2012
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4. CONCLUSION
The evaluation of information visualization is a very problematic task [24] [25]. Several
challenges could rise when researchers conduct an information visualization evaluation. These
challenges can be related to many factors: the context of use, participant gathering, data
collection, existence of evaluation environment (standard, reference tool for comparison, etc.).
As first future work, we intend to focus our attention on studying the existing method and metric
of evaluation of information visualization and semantic maps in order to evaluate our approach of
semantic navigation.
One of the biggest challenges of the visualization conception is that there is no strategy of “ideal”
visualization; the conception is always specific to the application. Different systems are efficient
for users having different backgrounds and needs (expert or novice, scientist or general
information). A universal model is difficult to be generalized.
As another perspective, we plan to construct a toolbox allowing users to select interactively the
visualization paradigm to be used in their maps and to make conversion between visualization
paradigms if they are not satisfied.
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