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.
Personalized web search using browsing history and domain knowledgeRishikesh Pathak
This document proposes a framework for improving personalized web search by constructing an enhanced user profile using both the user's browsing history and domain knowledge. The enhanced user profile is used to better suggest relevant web pages to the user based on their search query. An experiment found that suggestions made using the enhanced user profile performed better than using a standard user profile alone. The framework involves modeling the user, re-ranking search results, and displaying personalized results based on the enhanced user profile.
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.
IRJET- A Literature Review and Classification of Semantic Web Approaches for ...IRJET Journal
This document discusses using semantic web approaches for web personalization. It begins with an abstract that outlines how web personalization can help address the problem of information overload by recommending and filtering web pages according to a user's interests. The document then reviews related work on using ontologies and semantic web technologies for personalized e-learning, recommender systems, and other applications. It categorizes different semantic web approaches that have been used for web personalization, including their pros and cons. The overall purpose is to survey semantic web techniques for personalization and how they have been applied in previous research.
A Review: Text Classification on Social Media DataIOSR Journals
This document provides a review of different classifiers used for text classification on social media data. It discusses how social media data is often unstructured and contains users' opinions and sentiments. Various machine learning algorithms can be used to classify this social media text data, extracting meaningful information. The document focuses on describing Naive Bayes classifiers, which are commonly used for text classification tasks. It explains how Naive Bayes classifiers work by calculating the posterior probability that a document belongs to a certain class, based on applying Bayes' theorem with an independence assumption between features.
AN INTELLIGENT OPTIMAL GENETIC MODEL TO INVESTIGATE THE USER USAGE BEHAVIOUR ...ijdkp
The unexpected wide spread use of WWW and dynamically increasing nature of the web creates new
challenges in the web mining since the data in the web inherently unlabelled, incomplete, non linear, and
heterogeneous. The investigation of user usage behaviour on WWW is real time problem which involves
multiple conflicting measures of performance. These measures make not only computational intensive but
also needs to the possibility of be unable to find the exact solution. Unfortunately, the conventional methods
are limited to optimization problems due to the absence of semantic certainty and presence of human
intervention. In handling such data and overcome the limitations of conventional methodologies it is
necessary to use a soft computing model that can work intelligently to attain optimal solution.
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.
Recommendation generation by integrating sequential pattern mining and semanticseSAT Journals
Abstract As the Internet usage keeps increasing, the number of web sites and hence the number of web pages also keeps increasing. A recommendation system can be used to provide personalized web service by suggesting the pages that are likely to be accessed in future. Most of the recommendation systems are based on association rule mining or based on keywords. Using the association rule mining the prediction rate is less as it doesn’t take into account the order of access of the web pages by the users. The recommendation systems that are key-word based provides lesser relevant results. This paper proposes a recommendation system that uses the advantages of sequential pattern mining and semantics over the association rule mining and keyword based systems respectively. Keywords: Sequential Pattern Mining, Taxonomy, Apriori-All, CS-Mine, Semantic, Clustering
Personalized web search using browsing history and domain knowledgeRishikesh Pathak
This document proposes a framework for improving personalized web search by constructing an enhanced user profile using both the user's browsing history and domain knowledge. The enhanced user profile is used to better suggest relevant web pages to the user based on their search query. An experiment found that suggestions made using the enhanced user profile performed better than using a standard user profile alone. The framework involves modeling the user, re-ranking search results, and displaying personalized results based on the enhanced user profile.
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.
IRJET- A Literature Review and Classification of Semantic Web Approaches for ...IRJET Journal
This document discusses using semantic web approaches for web personalization. It begins with an abstract that outlines how web personalization can help address the problem of information overload by recommending and filtering web pages according to a user's interests. The document then reviews related work on using ontologies and semantic web technologies for personalized e-learning, recommender systems, and other applications. It categorizes different semantic web approaches that have been used for web personalization, including their pros and cons. The overall purpose is to survey semantic web techniques for personalization and how they have been applied in previous research.
A Review: Text Classification on Social Media DataIOSR Journals
This document provides a review of different classifiers used for text classification on social media data. It discusses how social media data is often unstructured and contains users' opinions and sentiments. Various machine learning algorithms can be used to classify this social media text data, extracting meaningful information. The document focuses on describing Naive Bayes classifiers, which are commonly used for text classification tasks. It explains how Naive Bayes classifiers work by calculating the posterior probability that a document belongs to a certain class, based on applying Bayes' theorem with an independence assumption between features.
AN INTELLIGENT OPTIMAL GENETIC MODEL TO INVESTIGATE THE USER USAGE BEHAVIOUR ...ijdkp
The unexpected wide spread use of WWW and dynamically increasing nature of the web creates new
challenges in the web mining since the data in the web inherently unlabelled, incomplete, non linear, and
heterogeneous. The investigation of user usage behaviour on WWW is real time problem which involves
multiple conflicting measures of performance. These measures make not only computational intensive but
also needs to the possibility of be unable to find the exact solution. Unfortunately, the conventional methods
are limited to optimization problems due to the absence of semantic certainty and presence of human
intervention. In handling such data and overcome the limitations of conventional methodologies it is
necessary to use a soft computing model that can work intelligently to attain optimal solution.
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.
Recommendation generation by integrating sequential pattern mining and semanticseSAT Journals
Abstract As the Internet usage keeps increasing, the number of web sites and hence the number of web pages also keeps increasing. A recommendation system can be used to provide personalized web service by suggesting the pages that are likely to be accessed in future. Most of the recommendation systems are based on association rule mining or based on keywords. Using the association rule mining the prediction rate is less as it doesn’t take into account the order of access of the web pages by the users. The recommendation systems that are key-word based provides lesser relevant results. This paper proposes a recommendation system that uses the advantages of sequential pattern mining and semantics over the association rule mining and keyword based systems respectively. Keywords: Sequential Pattern Mining, Taxonomy, Apriori-All, CS-Mine, Semantic, Clustering
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Classification-based Retrieval Methods to Enhance Information Discovery on th...IJMIT JOURNAL
The widespread adoption of the World-Wide Web (the Web) has created challenges both for society as a whole and for the technology used to build and maintain the Web. The ongoing struggle of information retrieval systems is to wade through this vast pile of data and satisfy users by presenting them with information that most adequately it’s their needs. On a societal level, the Web is expanding faster than we can comprehend its implications or develop rules for its use. The ubiquitous use of the Web has raised important social concerns in the areas of privacy, censorship, and access to information. On a technical level, the novelty of the Web and the pace of its growth have created challenges not only in the development of new applications that realize the power of the Web, but also in the technology needed to scale applications to accommodate the resulting large data sets and heavy loads. This thesis presents searching algorithms and hierarchical classification techniques for increasing a search service's understanding of web queries. Existing search services rely solely on a query's occurrence in the document collection to locate relevant documents. They typically do not perform any task or topic-based analysis of queries using other available resources, and do not leverage changes in user query patterns over time. Provided within are a set of techniques and metrics for performing temporal analysis on query logs. Our log analyses are shown to be reasonable and informative, and can be used to detect changing trends and patterns in the query stream, thus providing valuable data to a search service.
IRJET- A Novel Technique for Inferring User Search using Feedback SessionsIRJET Journal
This document proposes a novel technique to infer user search goals using feedback sessions. It aims to address limitations in existing approaches like noisy search results, small numbers of clicked URLs, and lack of consideration of user feedback. The proposed approach generates feedback sessions from user click logs, pre-processes the data, extracts keywords from restructured results, re-ranks the results based on keywords and user history, and categorizes the re-ranked results using predefined categories. The technique is evaluated using Average Precision, which compares it to other clustering and classification algorithms. The goal is to improve information retrieval by better representing user search interests and needs.
IRJET-Model for semantic processing in information retrieval systemsIRJET Journal
This document proposes a model for semantic information retrieval that improves upon traditional keyword matching approaches. It involves three main components:
1. A crawling and indexing component that identifies websites and pages, extracts metadata, and generates a knowledge graph through semantic annotation.
2. A processing component that analyzes user queries and profiles to understand search intent, calculates semantic similarity between queries and indexed documents, and determines result relevance.
3. A presentation component that displays search results to users through both simple and advanced search interfaces, prioritizing the most relevant information based on the above processing.
The model is intended to address deficiencies in current Cuban web search by better understanding natural language queries and the contextual meaning of information through semantic technologies
Projection Multi Scale Hashing Keyword Search in Multidimensional DatasetsIRJET Journal
The document discusses a novel method called ProMiSH (Projection and Multi Scale Hashing) for keyword search in multi-dimensional datasets. ProMiSH uses random projection and hash-based index structures to achieve high scalability and speedup of more than four orders over state-of-the-art tree-based techniques. Empirical studies on real and synthetic datasets of sizes up to 10 million objects and 100 dimensions show ProMiSH scales linearly with dataset size, dimension, query size, and result size. The method groups objects embedded in a vector space that are tagged with keywords matching a given query.
IRJET- Enhancing Prediction of User Behavior on the Basic of Web LogsIRJET Journal
The document discusses predicting user behavior based on web logs. It proposes using several algorithms to analyze web log data, including Apriori, KNN, FP-Growth, and an Improved Parallel FP-Growth algorithm. The algorithms are applied to preprocessed web log data to identify frequent patterns and items that provide insights into user behavior. Experimental results show the Improved Parallel FP-Growth algorithm provides higher mining efficiency and can handle large, growing datasets.
Scaling Down Dimensions and Feature Extraction in Document Repository Classif...ijdmtaiir
-In this study a comprehensive evaluation of two
supervised feature selection methods for dimensionality
reduction is performed - Latent Semantic Indexing (LSI) and
Principal Component Analysis (PCA). This is gauged against
unsupervised techniques like fuzzy feature clustering using
hard fuzzy C-means (FCM) . The main objective of the study is
to estimate the relative efficiency of two supervised techniques
against unsupervised fuzzy techniques while reducing the
feature space. It is found that clustering using FCM leads to
better accuracy in classifying documents in the face of
evolutionary algorithms like LSI and PCA. Results show that
the clustering of features improves the accuracy of document
classification
Context Driven Technique for Document ClassificationIDES Editor
In this paper we present an innovative hybrid Text
Classification (TC) system that bridges the gap between
statistical and context based techniques. Our algorithm
harnesses contextual information at two stages. First it extracts
a cohesive set of keywords for each category by using lexical
references, implicit context as derived from LSA and wordvicinity
driven semantics. And secondly, each document is
represented by a set of context rich features whose values are
derived by considering both lexical cohesion as well as the extent
of coverage of salient concepts via lexical chaining. After
keywords are extracted, a subset of the input documents is
apportioned as training set. Its members are assigned categories
based on their keyword representation. These labeled
documents are used to train binary SVM classifiers, one for
each category. The remaining documents are supplied to the
trained classifiers in the form of their context-enhanced feature
vectors. Each document is finally ascribed its appropriate
category by an SVM classifier.
IJRET : International Journal of Research in Engineering and TechnologyImprov...eSAT Publishing House
This document summarizes techniques for improving web search results through web personalization. It discusses how web usage mining can be used to optimize information by monitoring user interaction histories and profiles. The proposed system aims to reduce manual user feedback by implicitly gathering preferences from behaviors like click-through rates and dwell times. It introduces an algorithm that calculates new ranking values for websites based on keyword matches and time spent on pages, and swaps ranks accordingly. This system provides personalized search results by continuously updating rankings based on implicit user interactions.
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.
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.
IRJET-A Survey on Web Personalization of Web Usage MiningIRJET Journal
S.Jagan, Dr.S.P.Rajagopalan "A Survey on Web Personalization of Web Usage Mining", International Research Journal of Engineering and Technology (IRJET),Volume 2,issue-01 Mar-2015. e-ISSN:2395-0056, p-ISSN:2395-0072. www.irjet.net , published by Fast Track Publications
Abstract
Now a day, World Wide Web (www) is a rich and most powerful source of information. Day by day it is becoming more complex and expanding in size to get maximum information details online. However, it is becoming more complex and critical task to retrieve exact information expected by its users. To deal with this problem one more powerful concept is personalization which is becoming more powerful now days. Personalization is a subclass of information filtering system that seek to predict the 'ratings' or 'preferences' that a user would give to an items, they had not yet considered, using a model built from the characteristics of an item (content-based approaches or collaborative filtering approaches). Web mining is an emerging field of data mining used to provide personalization on the web. It consist three major categories i.e. Web Content Mining, Web Usage Mining, and Web Structure Mining. This paper focuses on web usage mining and algorithms used for providing personalization on the web.
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.
This document summarizes a research paper that proposes a framework for personalized web search using query log and clickthrough data. The framework implements a re-ranking approach that combines user search context and browsing behavior to generate personalized search results with high relevance. The framework consists of five components: a request handler, query processor, result handler, event handler, and response handler. The result handler applies a re-ranking approach using query log and clickthrough data to personalize search results before returning them to the user. An evaluation found the framework and re-ranking approach to be effective for personalized web search and information retrieval.
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.
A detail survey of page re ranking various web features and techniquesijctet
This document discusses techniques for page re-ranking on websites based on user behavior analysis. It describes how web usage mining involves analyzing web server logs to extract patterns in user behavior. Common techniques discussed for page re-ranking include Markov models, data mining approaches like clustering and association rule mining, and analyzing linked web page structures. The goal is to better understand user interests and predict future page access to improve information retrieval and optimize website design.
This document summarizes various approaches to web search personalization that have been proposed by researchers. It discusses 12 different approaches that use techniques such as building user profiles based on browsing history and click data, constructing personalized ontologies and taxonomies, re-ranking search results based on learned user interests, and updating user profiles based on implicit feedback during web browsing. The document concludes that personalized search is needed to better tailor search results to individual users and their contexts, and that continued research on innovative personalization techniques is important as the amount of online information grows.
Intelligent Semantic Web Search Engines: A Brief Survey dannyijwest
The World Wide Web (WWW) allows the people to share the information (data) from the large database repositories globally. The amount of information grows billions of databases. We need to search the information will specialize tools known generically search engine. There are many of search engines available today, retrieving meaningful information is difficult. However to overcome this problem in search engines to retrieve meaningful information intelligently, semantic web technologies are playing a major role. In this paper we present survey on the search engine generations and the role of search engines in intelligent web and semantic search technologies.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
This document summarizes a research paper on developing user profiles from search engine queries to enable personalized search results. It discusses how current search engines generally return the same results regardless of individual user interests. The paper proposes methods to construct user profiles capturing both positive and negative preferences from search histories and click-through data. Experimental results showed profiles including both preferences performed best by improving query clustering and separating similar vs. dissimilar queries. Future work aims to use profiles for collaborative filtering and predicting new query intents.
This document provides instruction on how to take Cornell notes, including:
1. Setting up notes with headings, date, topic in the left column and a large right column for details.
2. Taking notes during a lecture or reading in outline or narrative form in the right column.
3. Generating questions in the left column to prompt critical thinking.
4. Adding a 3-4 sentence summary at the bottom that recaps the key information.
The Cornell note taking method aims to help students organize ideas, review content, and study more effectively.
The document discusses conventions in thrillers and how the film aims to challenge some conventions while following others. It aims to portray isolation through a character's feelings rather than just physical isolation. It hopes to show the realities of drug use in a taboo way. The film is targeting audiences interested in independent films, strong narratives, realism and controversial topics like broken families and drug use in modern Britain. It believes a film festival and distributor like Microwave Films that works with low-budget British films could be a good fit to help attract audiences and achieve recognition.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Classification-based Retrieval Methods to Enhance Information Discovery on th...IJMIT JOURNAL
The widespread adoption of the World-Wide Web (the Web) has created challenges both for society as a whole and for the technology used to build and maintain the Web. The ongoing struggle of information retrieval systems is to wade through this vast pile of data and satisfy users by presenting them with information that most adequately it’s their needs. On a societal level, the Web is expanding faster than we can comprehend its implications or develop rules for its use. The ubiquitous use of the Web has raised important social concerns in the areas of privacy, censorship, and access to information. On a technical level, the novelty of the Web and the pace of its growth have created challenges not only in the development of new applications that realize the power of the Web, but also in the technology needed to scale applications to accommodate the resulting large data sets and heavy loads. This thesis presents searching algorithms and hierarchical classification techniques for increasing a search service's understanding of web queries. Existing search services rely solely on a query's occurrence in the document collection to locate relevant documents. They typically do not perform any task or topic-based analysis of queries using other available resources, and do not leverage changes in user query patterns over time. Provided within are a set of techniques and metrics for performing temporal analysis on query logs. Our log analyses are shown to be reasonable and informative, and can be used to detect changing trends and patterns in the query stream, thus providing valuable data to a search service.
IRJET- A Novel Technique for Inferring User Search using Feedback SessionsIRJET Journal
This document proposes a novel technique to infer user search goals using feedback sessions. It aims to address limitations in existing approaches like noisy search results, small numbers of clicked URLs, and lack of consideration of user feedback. The proposed approach generates feedback sessions from user click logs, pre-processes the data, extracts keywords from restructured results, re-ranks the results based on keywords and user history, and categorizes the re-ranked results using predefined categories. The technique is evaluated using Average Precision, which compares it to other clustering and classification algorithms. The goal is to improve information retrieval by better representing user search interests and needs.
IRJET-Model for semantic processing in information retrieval systemsIRJET Journal
This document proposes a model for semantic information retrieval that improves upon traditional keyword matching approaches. It involves three main components:
1. A crawling and indexing component that identifies websites and pages, extracts metadata, and generates a knowledge graph through semantic annotation.
2. A processing component that analyzes user queries and profiles to understand search intent, calculates semantic similarity between queries and indexed documents, and determines result relevance.
3. A presentation component that displays search results to users through both simple and advanced search interfaces, prioritizing the most relevant information based on the above processing.
The model is intended to address deficiencies in current Cuban web search by better understanding natural language queries and the contextual meaning of information through semantic technologies
Projection Multi Scale Hashing Keyword Search in Multidimensional DatasetsIRJET Journal
The document discusses a novel method called ProMiSH (Projection and Multi Scale Hashing) for keyword search in multi-dimensional datasets. ProMiSH uses random projection and hash-based index structures to achieve high scalability and speedup of more than four orders over state-of-the-art tree-based techniques. Empirical studies on real and synthetic datasets of sizes up to 10 million objects and 100 dimensions show ProMiSH scales linearly with dataset size, dimension, query size, and result size. The method groups objects embedded in a vector space that are tagged with keywords matching a given query.
IRJET- Enhancing Prediction of User Behavior on the Basic of Web LogsIRJET Journal
The document discusses predicting user behavior based on web logs. It proposes using several algorithms to analyze web log data, including Apriori, KNN, FP-Growth, and an Improved Parallel FP-Growth algorithm. The algorithms are applied to preprocessed web log data to identify frequent patterns and items that provide insights into user behavior. Experimental results show the Improved Parallel FP-Growth algorithm provides higher mining efficiency and can handle large, growing datasets.
Scaling Down Dimensions and Feature Extraction in Document Repository Classif...ijdmtaiir
-In this study a comprehensive evaluation of two
supervised feature selection methods for dimensionality
reduction is performed - Latent Semantic Indexing (LSI) and
Principal Component Analysis (PCA). This is gauged against
unsupervised techniques like fuzzy feature clustering using
hard fuzzy C-means (FCM) . The main objective of the study is
to estimate the relative efficiency of two supervised techniques
against unsupervised fuzzy techniques while reducing the
feature space. It is found that clustering using FCM leads to
better accuracy in classifying documents in the face of
evolutionary algorithms like LSI and PCA. Results show that
the clustering of features improves the accuracy of document
classification
Context Driven Technique for Document ClassificationIDES Editor
In this paper we present an innovative hybrid Text
Classification (TC) system that bridges the gap between
statistical and context based techniques. Our algorithm
harnesses contextual information at two stages. First it extracts
a cohesive set of keywords for each category by using lexical
references, implicit context as derived from LSA and wordvicinity
driven semantics. And secondly, each document is
represented by a set of context rich features whose values are
derived by considering both lexical cohesion as well as the extent
of coverage of salient concepts via lexical chaining. After
keywords are extracted, a subset of the input documents is
apportioned as training set. Its members are assigned categories
based on their keyword representation. These labeled
documents are used to train binary SVM classifiers, one for
each category. The remaining documents are supplied to the
trained classifiers in the form of their context-enhanced feature
vectors. Each document is finally ascribed its appropriate
category by an SVM classifier.
IJRET : International Journal of Research in Engineering and TechnologyImprov...eSAT Publishing House
This document summarizes techniques for improving web search results through web personalization. It discusses how web usage mining can be used to optimize information by monitoring user interaction histories and profiles. The proposed system aims to reduce manual user feedback by implicitly gathering preferences from behaviors like click-through rates and dwell times. It introduces an algorithm that calculates new ranking values for websites based on keyword matches and time spent on pages, and swaps ranks accordingly. This system provides personalized search results by continuously updating rankings based on implicit user interactions.
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.
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.
IRJET-A Survey on Web Personalization of Web Usage MiningIRJET Journal
S.Jagan, Dr.S.P.Rajagopalan "A Survey on Web Personalization of Web Usage Mining", International Research Journal of Engineering and Technology (IRJET),Volume 2,issue-01 Mar-2015. e-ISSN:2395-0056, p-ISSN:2395-0072. www.irjet.net , published by Fast Track Publications
Abstract
Now a day, World Wide Web (www) is a rich and most powerful source of information. Day by day it is becoming more complex and expanding in size to get maximum information details online. However, it is becoming more complex and critical task to retrieve exact information expected by its users. To deal with this problem one more powerful concept is personalization which is becoming more powerful now days. Personalization is a subclass of information filtering system that seek to predict the 'ratings' or 'preferences' that a user would give to an items, they had not yet considered, using a model built from the characteristics of an item (content-based approaches or collaborative filtering approaches). Web mining is an emerging field of data mining used to provide personalization on the web. It consist three major categories i.e. Web Content Mining, Web Usage Mining, and Web Structure Mining. This paper focuses on web usage mining and algorithms used for providing personalization on the web.
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.
This document summarizes a research paper that proposes a framework for personalized web search using query log and clickthrough data. The framework implements a re-ranking approach that combines user search context and browsing behavior to generate personalized search results with high relevance. The framework consists of five components: a request handler, query processor, result handler, event handler, and response handler. The result handler applies a re-ranking approach using query log and clickthrough data to personalize search results before returning them to the user. An evaluation found the framework and re-ranking approach to be effective for personalized web search and information retrieval.
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.
A detail survey of page re ranking various web features and techniquesijctet
This document discusses techniques for page re-ranking on websites based on user behavior analysis. It describes how web usage mining involves analyzing web server logs to extract patterns in user behavior. Common techniques discussed for page re-ranking include Markov models, data mining approaches like clustering and association rule mining, and analyzing linked web page structures. The goal is to better understand user interests and predict future page access to improve information retrieval and optimize website design.
This document summarizes various approaches to web search personalization that have been proposed by researchers. It discusses 12 different approaches that use techniques such as building user profiles based on browsing history and click data, constructing personalized ontologies and taxonomies, re-ranking search results based on learned user interests, and updating user profiles based on implicit feedback during web browsing. The document concludes that personalized search is needed to better tailor search results to individual users and their contexts, and that continued research on innovative personalization techniques is important as the amount of online information grows.
Intelligent Semantic Web Search Engines: A Brief Survey dannyijwest
The World Wide Web (WWW) allows the people to share the information (data) from the large database repositories globally. The amount of information grows billions of databases. We need to search the information will specialize tools known generically search engine. There are many of search engines available today, retrieving meaningful information is difficult. However to overcome this problem in search engines to retrieve meaningful information intelligently, semantic web technologies are playing a major role. In this paper we present survey on the search engine generations and the role of search engines in intelligent web and semantic search technologies.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
This document summarizes a research paper on developing user profiles from search engine queries to enable personalized search results. It discusses how current search engines generally return the same results regardless of individual user interests. The paper proposes methods to construct user profiles capturing both positive and negative preferences from search histories and click-through data. Experimental results showed profiles including both preferences performed best by improving query clustering and separating similar vs. dissimilar queries. Future work aims to use profiles for collaborative filtering and predicting new query intents.
This document provides instruction on how to take Cornell notes, including:
1. Setting up notes with headings, date, topic in the left column and a large right column for details.
2. Taking notes during a lecture or reading in outline or narrative form in the right column.
3. Generating questions in the left column to prompt critical thinking.
4. Adding a 3-4 sentence summary at the bottom that recaps the key information.
The Cornell note taking method aims to help students organize ideas, review content, and study more effectively.
The document discusses conventions in thrillers and how the film aims to challenge some conventions while following others. It aims to portray isolation through a character's feelings rather than just physical isolation. It hopes to show the realities of drug use in a taboo way. The film is targeting audiences interested in independent films, strong narratives, realism and controversial topics like broken families and drug use in modern Britain. It believes a film festival and distributor like Microwave Films that works with low-budget British films could be a good fit to help attract audiences and achieve recognition.
This document is an introduction to a book about love. It discusses how love is something we all seek in our relationships, but that true love begins from within oneself. True love is a state of being, not confined to relationships with others. Learning to love oneself is key to being able to share love freely with others without need, attachment or suffering. The following chapters will offer suggestions for ways to discover and manifest the love within through practices like self-care, acceptance and living in the present moment.
Principios para el desarrollo de las buenas practicas pedagogicas de las TIC...Kari L
Las TIC deben usarse de manera socioconstructiva para que los estudiantes construyan su propio conocimiento resolviendo problemas en colaboración. Los ordenadores por sí solos no mejoran la enseñanza, depende del método y las actividades. Las TIC permiten a los estudiantes manipular y compartir grandes volúmenes de información, por lo que deben desarrollar habilidades para tomar decisiones y resolver problemas. También posibilitan la comunicación entre estudiantes distantes para trabajar en grupo sobreactividades y tareas.
Una encuesta es un estudio observacional en el que el investigador busca recopilar datos por medio de un cuestionario previamente diseñado, sin modificar el entorno ni controlar el proceso que está en observación (como sí lo hace en un experimento). Los datos se obtienen realizando un conjunto de preguntas normalizadas dirigidas a una muestra representativa o al conjunto total de la población estadística en estudio, integrada a menudo por personas, empresas o entes institucionales, con el fin de conocer estados de opinión, características o hechos específicos. El investigador debe seleccionar las preguntas más convenientes, de acuerdo con la naturaleza de la investigación.
El documento describe varias nuevas técnicas e investigaciones en medicina. Se ha desarrollado una enzima llamada prolina deshidrogenasa que puede ayudar a prevenir el cáncer. También se ha creado una sangre artificial similar a la hemoglobina que podría usarse como sustituto de la sangre. Además, se ha inventado una tirita digital pequeña que puede medir signos vitales como la frecuencia cardíaca y enviar los datos a un ordenador para monitorear pacientes de forma remota.
Tic contenidos y escuela planes_ programas y proyectos para el trabajo con ti...yo el barbas.
Este documento discute el uso de las TIC en las escuelas. Propone que tanto el profesorado como el alumnado necesitan formarse en competencias digitales para integrar las TIC de manera efectiva. Describe tres modelos de integración de las TIC (cerrado, abierto y mixto) y sugiere que el modelo mixto sería el más adecuado. También presenta principios educativos de las TIC según Manuel Area, incluyendo que las TIC deben usarse para apoyar procesos de aprendizaje socioconstructivos y como herram
El documento habla sobre la contaminación ambiental. Explica los efectos, causas y diferentes tipos de contaminación como la del aire, agua, suelo y alimentos. También describe los contaminantes químicos, físicos y biológicos y cómo estos afectan los ecosistemas.
This document outlines the key financial responsibilities of not-for-profit board members, including fiscal oversight, accounting systems and controls, financial statements, audits, and compliance with regulations. It discusses the board's duties of care, loyalty and obedience. The board is responsible for overseeing accounting, internal controls, financial reporting, hiring an independent auditor, and ensuring compliance with laws and regulations.
El documento habla sobre la inclusión de las competencias básicas en el currículum escolar. Explica que las competencias básicas se han introducido para adaptar la educación a los cambios sociales y preparar a los estudiantes para la vida y el aprendizaje continuo. Define las competencias básicas y sus componentes, y ofrece recomendaciones sobre cómo desarrollar un currículum centrado en competencias, incluyendo el trabajo interdisciplinario y el uso de métodos activos de enseñanza. También cubre cómo integrar las competencias
1. O documento discute como a Administração Pública tem se adaptado ao contexto da "modernidade líquida", onde há maior fluidez do capital e demandas por Estados mais eficientes.
2. Analisa como o Estado de bem-estar social surgiu para atender demandas sociais, mas acabou criando estruturas burocráticas pesadas que oneram o capital.
3. Defende que, na atualidade, é necessária uma Administração Pública mais consensual e participativa, que busque soluções flexíveis aos problemas, ao invés
This document is a thesis presented to obtain the title of Commercial Engineer and External Integration Director. It discusses the production and commercialization of soybean meal to the Colombian market under the maquila regime. It includes chapters on general soybean information, market study, engineering project design, and economic/financial evaluation. The project proposes establishing a processing plant in Ecuador to import soybeans from Colombia under maquila, extract soybean meal, and export the product.
Este documento apresenta os Parâmetros Curriculares Nacionais para o ensino de Língua Portuguesa nos terceiro e quarto ciclos do ensino fundamental. Ele discute a natureza da linguagem e do ensino de Língua Portuguesa, definindo seus objetivos gerais e conteúdos. A segunda parte especifica os objetivos, conteúdos, orientações didáticas e critérios de avaliação para esses ciclos, abordando também a relação entre o ensino de Língua Portuguesa e novas tecnologias.
El documento presenta los resultados de 5 ejemplos de estudios realizados por estudiantes de la Escuela Académico Profesional de Ingeniería Geológica de la Universidad Nacional Mayor de San Marcos. Cada ejemplo incluye datos cuantitativos y su respectivo análisis porcentual, mostrando en la mayoría de casos que la categoría con mayor porcentaje fue la de rocas metamórficas, alumnos de San Juan de Lurigancho, mineral plagioclasa, estructura estratificaciones y equipo varilla de luz de emer
Este documento presenta una introducción al sistema de gestión de bases de datos MySQL. MySQL es un gestor de bases de datos relacional, multihilo y multiusuario que se utiliza ampliamente en Internet debido a que es gratuito para aplicaciones no comerciales. El documento describe brevemente el historial de MySQL, sus características principales como el soporte de múltiples tipos de datos y lenguajes de programación, y sus usos comerciales y versiones disponibles.
El documento presenta varios avances tecnológicos recientes como un robot flexible inspirado en los pulpos, músculos artificiales más fuertes que el acero, un dispositivo que permite a un robot leer órdenes mentales sin implantes cerebrales, y un casco de realidad virtual que simula los cinco sentidos. También describe el desarrollo de sangre artificial que podría almacenarse de forma deshidratada y fabricarse como donación universal.
Y-PEER Newsletter on 10 Days of Activism 2010Y-PEER Hacioglu
Y-PEER organized first 10 Days of Activism in 2010.
You may check the stories and activities that were done during 10 DoA 2010.
If you like to take part in 10 DoA 2011 which will take part between 1 and 10 July you can check 10 Things to Know about 10 DoA document at http://www.slideshare.net/FatmaHacioglu1/10-things-to-know-about-10-doa?from=share_email
Este documento explica paso a paso cómo construir una tabla de datos agrupados. Muestra cómo calcular los intervalos reales y aparentes, y agregar columnas para las medidas de tendencia central y dispersión como la frecuencia absoluta, frecuencia relativa y frecuencia relativa acumulada. Finalmente, explica cómo usar estas tablas para crear histogramas y ojivas.
Este documento explica paso a paso cómo construir una tabla de datos agrupados. Muestra cómo calcular los intervalos, las frecuencias absolutas y relativas, y las frecuencias acumuladas. También cubre cómo representar gráficamente los datos agrupados usando un histograma y una ojiva.
CRM es una estrategia de negocios centrada en el cliente, no un software. Implica entender y anticipar las necesidades de los clientes actuales y potenciales para mejorar las relaciones con los clientes. Una implementación efectiva de CRM requiere cambios en las estrategias, funciones y procesos de una empresa antes de adoptar soluciones tecnológicas para apoyar la nueva estrategia.
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.
The document describes a proposed model for representing user profiles using ontologies for personalized web information gathering. The model uses both a world knowledge base (encoded from the Library of Congress Subject Headings) and a user's local instance repository to construct personalized ontologies representing the user's concept models and background knowledge. The proposed model is compared against existing benchmark models through experiments using a large standard dataset, and results show the proposed model improves web information gathering performance.
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.
An effective search on web log from most popular downloaded contentijdpsjournal
A Web page recommender system effectively predicts the best related web page to search. While search
ing
a word from search engine it may display some unnecessary links and unrelated data’s to user so to a
void
this problem, the con
ceptual prediction model combines both the web usage and domain knowledge. The
proposed conceptual prediction model automatically generates a semantic network of the semantic Web
usage knowledge, which is the integration of domain knowledge and web usage i
nformation. Web usage
mining aims to discover interesting and frequent user access patterns from web browsing data. The
discovered knowledge can then be used for many practical web applications such as web
recommendations, adaptive web sites, and personali
zed web search and surfing
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.
Ontological approach for improving semantic web search resultseSAT Journals
Abstract we propose personalized information system to provide more user-oriented information considering context information such as a personal profile based, location based and click based. Our system can provide associated search results from relations between the objects using context ontologies modeling created by the categorized layers data. Based on the similarities between item descriptions and user profiles, and the semantic relations between concepts, content based and collaborative recommendation models are supported by the system. User defined rules based on the ontology description of the service and interoperates within any service domain that has an ontology description. Keywords- Ontology; Semantic Web; RDF;OWL
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
A Study of Pattern Analysis Techniques of Web Usageijbuiiir1
Web mining is the most important application of data mining techniques to extract knowledge from web data including web document, hyperlinks between documents, usage logs of web sites etc. Web mining has been explored to a vast degree and different techniques have been proposed for a huge variety of applications that includes search engine enhancement, optimization of web services, Business Intelligence, B2B and B2C business etc. Most research on web mining has been from a �process-centric� point of view which defined web mining as a sequence of tasks. In this paper, we highlight the significance of studying the evolving nature of the web pattern analysis (WPA). Web usage mining is used to discover interesting user navigation patterns and can be applied to many real-world problems, such as improving web sites/pages. A Web usage mining system performs five major tasks: i) data collection ii) information filtering iii) pattern discovery iv) pattern analysis and visualization techniques, and v) Knowledge Query Mechanism (KQM). Each task is explained in detail and its related technologies are introduced. The web mining research is a converging research area from several research communities, such as database system, information retrieval, information extraction and artificial intelligence. In this paper we implement how web usage mining techniques can be applied for the customization i.e. web visualization
Web search engines help users find useful information on the WWW. However, when the same
query is submitted by different users, typical search engines return the same result regardless of who
submitted the query. Generally, each user has different information needs for his/her query. Therefore,
the search results should be adapted to users with different information needs. So, there is need of
several approaches to adapting search results according to each user’s need for relevant information
without any user effort. Such search systems that adapt to each user’s preferences can be achieved by
constructing user profiles based on modified collaborative filtering with detailed analysis of user’s
browsing history.
There are three possible types of web search system which can provide personalized
information: (1) systems using relevance feedback, (2) systems in which users register their interest, and
(3) systems that recommend information based on user’s history. In first technique, users have to provide
feedback on relevant or irrelevant judgments which is time consuming and the second one needs
registration of users with their static interests which need extra effort from user. So, the third technique
is best in which users don’t have to give explicit rating; relevancy automatically tracked by user
behavior with search results and history of data usage. It doesn’t require registration of interests; it
captures changing interests of user dynamically by itself. The result section shows that user’s browsing
history allows each user to perform more fine-grained search by capturing changes of each user’s
preferences without any user effort. Users need less time to find the relevant snippet in personalized
search results compared to original results
Web search engines help users find useful information on the WWW. However, when the same query is submitted by different users, typical search engines return the same result regardless of who submitted the query. Generally, each user has different information needs for his/her query. Therefore, the search results should be adapted to users with different information needs. So, there is need of
several approaches to adapting search results according to each user’s need for relevant information without any user effort. Such search systems that adapt to each user’s preferences can be achieved by constructing user profiles based on modified collaborative filtering with detailed analysis of user’s browsing history. There are three possible types of web search system which can provide personalized information: (1) systems using relevance feedback, (2) systems in which users register their interest, and (3) systems that recommend information based on user’s history. In first technique, users have to provide feedback on relevant or irrelevant judgments which is time consuming and the second one needs
registration of users with their static interests which need extra effort from user. So, the third technique is best in which users don’t have to give explicit rating; relevancy automatically tracked by user behavior with search results and history of data usage. It doesn’t require registration of interests; it captures changing interests of user dynamically by itself. The result section shows that user’s browsing history allows each user to perform more fine-grained search by capturing changes of each user’s
preferences without any user effort. Users need less time to find the relevant snippet in personalized
search results compared to original results.
Iaetsd web personalization a general surveyIaetsd Iaetsd
This document provides an overview of web personalization and related techniques. It discusses how web personalization aims to satisfy user requirements by personalizing web data based on a user's interests, social category, and context. Common approaches to web personalization include rule-based systems, content-based filtering using user profiles, and collaborative filtering. The document also surveys previous research that has used ontologies and user profiling to enable more personalized web experiences.
The size of the Internet enlarging as per to grow the users of search providers continually demand search
results that are accurate to their wishes. Personalized Search is one of the options available to users in
order to sculpt search results based on their personal data returned to them provided to the search
provider. This brings up fears of privacy issues however, as users are typically anxious to revealing
personal info to an often faceless service provider along the Internet. This work proposes to administer
with the privacy issues surrounding personalized search and discusses ways that privacy can be improved
so that users can get easier with the dismissal of their personal information in order to obtain more precise
search results.
This document summarizes a research paper that proposes a novel framework for personalized web search using query log and clickthrough data. The framework implements a re-ranking approach to generate personalized search results with high relevance. It derives an extended set of user preferences and concepts based on extracted data from query logs and clickthrough information. An evaluation found the framework and re-ranking approach to be highly effective for personalized search and information retrieval.
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.
`A Survey on approaches of Web Mining in Varied Areasinventionjournals
There has been lot of research in recent years for efficient web searching. Several papers have proposed algorithm for user feedback sessions, to evaluate the performance of inferring user search goals. When the information is retrieved, user clicks on a particular URL. Based on the click rate, ranking will be done automatically, clustering the feedback sessions. Web search engines have made enormous contributions to the web and society. They make finding information on the web quick and easy. However, they are far from optimal. A major deficiency of generic search engines is that they follow the ‘‘one size fits all’’ model and are not adaptable to individual users.
1. The document describes a search engine scraper that extracts data from websites, summarizes the extracted information, and converts it into a relevant result for users.
2. The search engine scraper works in three stages: extraction of data from website content, summarization of the extracted data using natural language processing techniques, and conversion of the summarized data into a meaningful format for users.
3. The summarization stage uses natural language toolkit processing libraries to determine sentence similarity, assign weights to sentences, and select sentences with higher ranks to include in the summary.
This document proposes a new system called "Combi" that combines three web mining techniques (web content mining, web structure mining, and web usage mining) with a learner's profile for personalized e-learning. Combi aims to help learners find the most suitable information for their needs without sifting through long search results. It does this by discovering learning behavior patterns and building feedback and motivation systems. The system architecture and algorithm are described. Results show Combi has better performance than an existing related system, with higher precision and random index scores for most topic queries tested.
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journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJCER, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, research and review articles, IJCER Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathematics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer review journal, indexed journal, research and review articles, engineering journal, www.ijceronline.com, research journals,
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journal of engineering, online Submission
This document summarizes an article from the International Journal of Engineering Research and Applications titled "Explicit User Profiles for Semantic Web Search Using XML" by C. Srinvas.
The article discusses how to build explicit user profiles using XML to personalize semantic web searches. It covers collecting user data, inferring user profiles, and representing profiles. The key approach is to define an ontology of topics and annotate concepts with interest scores that are continuously updated based on user behavior using spreading activation methods. This builds ontological user profiles that represent user interests to improve search accuracy.
The document summarizes a research paper on DBLP Search Support Engine (SSE), a system that aims to provide intelligent and personalized search beyond traditional search engines. It extracts users' research interests based on publication frequency and recency using interest retention models. The system represents users and their interests using RDF and provides additional functionalities like query refinement, domain analysis and tracking based on users' interests. Future work includes improving the interest prediction model and providing a unified architecture for different system functions.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
CAKE: Sharing Slices of Confidential Data on BlockchainClaudio Di Ciccio
Presented at the CAiSE 2024 Forum, Intelligent Information Systems, June 6th, Limassol, Cyprus.
Synopsis: Cooperative information systems typically involve various entities in a collaborative process within a distributed environment. Blockchain technology offers a mechanism for automating such processes, even when only partial trust exists among participants. The data stored on the blockchain is replicated across all nodes in the network, ensuring accessibility to all participants. While this aspect facilitates traceability, integrity, and persistence, it poses challenges for adopting public blockchains in enterprise settings due to confidentiality issues. In this paper, we present a software tool named Control Access via Key Encryption (CAKE), designed to ensure data confidentiality in scenarios involving public blockchains. After outlining its core components and functionalities, we showcase the application of CAKE in the context of a real-world cyber-security project within the logistics domain.
Paper: https://doi.org/10.1007/978-3-031-61000-4_16
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
HCL Notes and Domino License Cost Reduction in the World of DLAU
Kp3518241828
1. Mohd.Ahmed.Ali et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 5, Sep-Oct 2013, pp.1824-1828
RESEARCH ARTICLE
www.ijera.com
OPEN ACCESS
A Personalized User Concept Model For Web Information
Gathering
S.Swapna, Mohd.Ahmed.Ali
( Assistant Professor,IT,Aurora Technological and Research Institute,Hyd )
(M.TECH(Web Technology),Aurora Technological and Research Institute,Hyd )
ABSTRACT
Nowadays It has become very easy to access information from internet via World Wide Web. If we want any
information through search engine they do not deliver the relevant information because they are programmed as
one size fits all. Ironically the very vast size of this collection has become an obstacle for information retrieval. It
is very logical and reasoning to personalize the retrieval system specific to the preference of a user.
However,when representing user profiles,many models have utilized only knowledge from either global
knowledge base or a user local information This paper work contribute in improving the accuracy of
information gather to personalize the user profile by combining the knowledge base and user local instance
repository with 2D ontology mining method is introduced: Specificity and Exhaustivity. This concept model
cannot be proven in laboratories; many web ontologists have observed it in a user behavior the results show that
this ontology model is successful.
Keywords - Local instance repository, Ontological user profiles, Personalization, Semantic relations, User
context
I.
INTRODUCTION
World Wide Web (W.W.W) is a magnificent
and vast portal for acquiring , gathering and retrieval
information from the infinite information present on
the web. Web information is available in a great range
of topics and categories. How to collect the required
information from the collected information is a
challenging task. The Web users expect more
intelligent systems (or agents) to gather the useful
information from the huge size of Web related data
sources to meet their information needs. The Rapid
growth of documents in the Web makes it difficult to
determine the most relevant documents for a particular
user, given a general query. User performs searching
to access relevant document for himself. Therefore,
aspecific system should be there to personalize the
information retrieved by user according to his
preference. User profiles reflect the interests of users
[5]. User profiles concepts are used in gathering web
information to capture user information needs in order
to get personalized web information for users. For this
purpose only, user profiles are created for user
background knowledge description.
Global analysis uses only existing global
knowledge bases for user background knowledge
discovery. Generally used knowledge bases include
generic ontologies , thesauruses (e.g., digital libraries),
and online knowledge bases (e.g., online
categorizations). The global analysis techniques
effectively produce good performance for user
background knowledge extraction.However, global
analysis is limited to the quality of the used
knowledge base.
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Local analysis investigates the user local information
and observes user behavior in user profiles. For
example, Li and Zhong [6] discovered taxonomical
patterns from the users’local text documents to learn
ontologies from user profiles. Alternatively, Sekine
and Suzuki [14] analyzed the query logs to discover
user background knowledge. In some works, such as
[13],users were provided with a set of documents and
asked for relevance feedback from that documents.
User background knowledge was discovered from
this feedback for user profiles. However, because
local analysis techniques rely on data mining or old
classification techniques for knowledge discovery,
occasionally the discovered results contain noisy and
unrelevant information. As a result, local analysis
suffers from ineffectiveness at capturing the relevant
user information.
From this, we can hypothesize that user
background knowledge can give better result if we can
collaborate global and local analysis within a hybrid
model. The Information formalized in a global
knowledgebase will constrain the background
knowledge discovered from the user local
information.
II.
RELATED WORK
2.1 Learning Personalized Ontological Context
Effective personalization of relevant
information access involves two important
challenges: accurately identifying the user context
and organizing the information in such a way that it
matches the particular context[9]. Since the
acquisition of user interests is an essential element in
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ISSN : 2248-9622, Vol. 3, Issue 5, Sep-Oct 2013, pp.1824-1828
identifying the user context, most personalized search
systems employ a user concept modeling component.
Global knowledge base has been used by
many previous or existing models to learn ontologies
for web information gathering. For example, Gauch et
al. [2] and Sieg et al. [9] learned personalized
ontologies from the Open Directory Project to specify
users’ interests in web search. Wikipedia used by
Downey et al. [12] to understand underlying user
interests in queries. These works effectively
discovered the user background knowledge; but , their
performance was limited by the quality of the global
knowledge bases.
Learning personalized ontologies, required
many works mining of user background knowledge
from the user local information.Li and Zhong [6] used
pattern recognition and association rule mining
techniques to discover the background knowledge
from user local documents for ontology construction.
Zhong [6] proposed a domain personalized ontology
learning approach that will employed the various data
mining and natural language techniques. Navigli et
al. [3] developed the OntoLearn technique to discover
semantic concepts and relations from web documents.
Finally, captured user information at the sentence
level rather than the document level, represented user
profiles by the Conceptual Ontological Graph. The
use of data mining techniques in these models leads to
user background knowledge being discovered.
However, the knowledge collected in these works
contained noise and unrelated data.
Additionally, ontologies were used for many
works to improve the performance of knowledge
discovered.Uptil,concept based search,keyword based
search is available but the URL searching is text
based online searching which is different than
available search.
2.2
Techniques for Generating User Concept
Profile
The user’s intent for information seeking.
We propose to model a user’s concept model for
information access context by seamlessly integrating
knowledge from the world knowledge and local
instance repository. In our framework, context is
implicitly defined through the notion of ontological
user profiles, which are updated over time to reflect
changes in user interests[9]. This representation our
approach differentiate from previous work which
depends on the context information to be explicitly
defined.
When acquiring user concept profiles, the
content and applications are taken into consideration
,since user interests are approximate and it is
suggested that it can be represented by ontologies[15]
. User profile techniques can be categorized into three
groups: 1) Interviewing 2) Non-interviewing 3) Semiinterviewing.
The interviewing technique are done
manually by asking the questions and by using the
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user trained datasets. Users will read the training sets
of documents and then assign positive or negative
feedback based on user‘s personal interests.e.g. TREC
model was used to acquire training set manually[13].
The topic coverage of TREC profiles is limited. But it
provides more accuracy,but weak in terms of
precision.
In Non-interviewing technique there is no
involvement of user, it is based on the observation at
user‘s behavior, user‘s interests and preferences
which are described by a set of weighted subjects,
learned from the user‘s browsing history.When an
OBIWAN agent receives the search results based on a
given topic, it filters and reranks the results based on
their semantic similarity with the subjects. Then the
similar documents will be kept aside, then awarded
and reranked higher on the result list. e.g. Category
model.
Semi-interviewing technique the user
involvement is very less, in which user profiles are
acquired from the web by employing a web search
engine. The noisy and uncertain terms will referred to
the paradoxical concepts. e.g. Web mining model.
Using web documents for training sets has severe
drawback: web information has much more noise and
uncertainties. As a result, the web user profiles are
satisfactory in terms of recall, but weak in terms of
precision. There is no negative training set generated
by this model. In ontology model ,semi-interviewing
technique is used.
Fig.1.Shows the user context model which
represents the users intent for information seeking
We propose to model a user’s information access
context by seamlessly integrating knowl-edge from
the immediate and past user activity as well as
knowledge from a pre-existing ontology as an explicit
representation of the domain of interest[9].This
representation distinguishes our approach from
previous work which depends on the context
information to be explicitly defined.
Fig .1: User Context Model[9]
III.
CONSTRUCTION OF
PERSONALIZED ONTOLOGICAL
PROFILES
In the present framework, the user context is
represented using an ontological user profile, which is
an annotated instance of reference ontology[9].Each
personalized ontological user profile is initially an
instance of the reference ontology.Thus,the user
context is maintained and updated incrementally
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www.ijera.com
based on user’s ongoing behavior.
User personalized ontologies are a
conceptualization model, that formally describes and
specifies user background knowledge. From
observations in our daily life, we found that web users
might have different expectations for the same search
query. For example,a person may demand different
information for various medical aids[15]. Sometimes
even the same user may have different expectations
for the same search query if applied in a different
situation. Based on this observation, an assumption is
made that web users have a personal concept model
for their information needs. Therefore, a user concept
model for different information need is suggested.
3.1 Representation Of World Knowledge Base
World
knowledge
base
contains
commonsense knowledge possessed by people and
acquired by their experience and education.World
knowledge base contains exhaustive range of
topics,because users may come from different
backgrounds. Also, “world knowledge is necessary
for lexical analysis and referential disambiguation,
including establishing co reference relations and
resolving ellipsis as well as for establishing
connectivity of the discourse and adherence of the
text to the text producer’s goal and plans”[15]. In this
proposed model, user background knowledge is
extracted from web.
3.2 Creation of Ontology Environment
Creation
of
Ontology
learning
environment(OLE) involes the subjects of user
interest which are extracted from the WKB via user
interaction. A tool called Ontology Learning
Environment (OLE) is used to assist users with such
interaction[1].Depending upon the topic, the
interesting subjects consisting of two sets:
positivesubjects are the concepts relevant to the
information need, and negative subjects are the
concepts resolving paradoxical or ambiguous
interpretation of the information need. Thus, for a
given specific topic, the OLE provides the users with
a set of candidates to identify positive and negative
subjects. These candidate can select the subjects
which are extracted from the WKB.
Fig. 2 is a screen-shot of the OLE for the
sample topic “Economic espionage.” The subjects
listed on the top-left panel of the OLE are the
candidate subjects presented in hierarchical form.
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Fig. 2: Ontology learning environment[1]
From these candidates, the user selects
positive subjects for the topic. The user-selected
positive subjects are presented on the top-right panel
in hierarchical form. The candidate negative subjects
are the descendants of the user-selected positive
subjects. They are shown on the bottom-left panel.
From these negative candidates, the user selects
tnegative subjects. These user-selected negative
subjects are listed on the bottom-right panel (e.g.,
“Political ethics” and “Student ethics”)[1]. Note that
for the completion of the structure, some positive
subjects (e.g., “Ethics,” “Crime,” “Commercial
crimes,” and “Competition Unfair”)are also included
on the bottom-right panel with the negative
subjects[15]. These positive subjects will not be
included in the negative set.The remaining
candidates, which are not fed back as either positive
or negative from the user, become the neutral subjects
to the given topic.
An ontology is then constructed for the given topic
using these user fed back subjects. The structure of
the ontology is based on the semantic relations
linking these subjects in the WKB. The ontology
contains three types of knowledge:positive subjects,
negative subjects, and neutral subjects.
IV.
TWO DIMENSIONAL ONTOLOGY
MINING
Two dimension Ontology mining method is
used for mining data. Specificity describes a subject’s
focus on a given topic where as Exhaustivity restricts
a subjects semantic space dealing with the topic. This
two methods aims to investigate the subjects focus
and the strength of their associations in ontology.The
knowledge formalized in a global knowledge base
will contain the background knowledge discoverd
from the user local repository. Such a personalized
user concept model should produce a superior
representation of user profiles for web information
gathering.
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4. Mohd.Ahmed.Ali et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 5, Sep-Oct 2013, pp.1824-1828
Algorithm:
Algorithm works based on personalized
ontology. It traverses all the nodes and identifies
nodes with strongest and weakest specificity. The
semantic specificity of a subject is measured based on
the investigation of subject locality that comes from
ontology and relationship among concepts.
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provides the taxonomic structure for the personalized
ontology. The user background knowledge is
collected from the user local instance repository.
From the figure, we can hypothesize that user
background knowledge can be better discovered and
represented if we can integrate global and local
analysis within a hybrid model.
Fig 3: user concept model Architecture[15]
REFERENCES
[1]
Algorithm 1. Analyzing semantic specificity[1]
4.1 Topic Specificity Of Subject
The topic specificity of a subject is
investigated, based on the user background
knowledge discovered from user local history or
information.
4.2 User Background Local Instance Repository
The User background knowledge can be
discovered from the user collection of local
information , such as a user’s stored documents,
browsed web pages, and composed/received emails
[6]. The ontological user profiles constructed in
Section 3 has only subject labels and semantic
relations specified. In this section, we populate the
ontology with the instances generated from user local
infor-mation collections. Such a collection of the
user’s local instance repository (LIR). The topic
specificity of a subject is evaluated based on the
instance topic strength of its citing URLS. With
respect to the absolute specificity, the topic specificity
can also be called relative specificity
[2]
[3]
[4]
[5]
[6]
V.
ONTOLOGY MODEL
ARCHITECTURE
The proposed user concept ontology model
aims to discover user back-ground knowledge and
learns personalized ontologies to represent user
concept profiles.
Fig. 3 illustrates the architecture of the user
concept model. A personalized ontology is
constructed, according to a given topic. Two
knowledge resources, the global world knowledge
base and the user’s local instance repository, are
utilized in these model. The world knowledge base
www.ijera.com
[7]
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Authors Profile
First Author - S.Swapna recived her M.Sc
Computer Science in 2007 from Reddy women’s
College Narayanguda and M.Tech in Web
Technologies from Aurora’s Technological and
Research Institute, JNTUH. Her area of expertise
includes
Operating
system,
Database
and
Management System (DBMS),. She is working as
Assistant Professor in department of Information
Technology at Aurora’s Technological and Research
Institute, Hyderabad. JNTUHHyderabad,
SecondAuthor – Mohd.Ahmed.Ali, M.Tech
(W.T), Aurora’s Technological and Research
Institute, JNTUH yderabad, Andhra Pradesh, pin
code-500035, India
www.ijera.com
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