The document describes the BioNav system, which categorizes large numbers of biomedical literature search results from PubMed using the MeSH concept hierarchy. BioNav constructs an initial navigation tree by attaching PubMed citations to relevant MeSH concepts. It then reduces this tree by removing empty nodes. Unlike static navigation interfaces, BioNav dynamically selects a small subset of concept nodes to display at each step based on estimated user navigation cost. This allows users to efficiently explore concepts of interest and find relevant citations from large result sets.
PERFORMANCE EVALUATION OF STRUCTURED AND SEMI-STRUCTURED BIOINFORMATICS TOOLS...ijseajournal
This document evaluates the performance of structured and semi-structured tools for accessing bioinformatics databases. It compares the Sequence Retrieval System (SRS) and Entrez search tools for structured data retrieval to Perl and BioPerl programs for semi-structured data retrieval. The study retrieves gene information from the European Bioinformatics Institute and National Centre for Biotechnology Information databases using each method. It finds that semi-structured tools provide an alternative to structured tools, though each approach has advantages and disadvantages for certain types of queries.
PERFORMANCE EVALUATION OF STRUCTURED AND SEMI-STRUCTURED BIOINFORMATICS TOOLS...ijseajournal
This document evaluates the performance of structured and semi-structured tools for accessing bioinformatics databases. It compares the Sequence Retrieval System (SRS) and Entrez search tools for structured data retrieval to Perl and BioPerl programs for semi-structured data retrieval. The study retrieves gene information from the European Bioinformatics Institute and National Center for Biotechnology Information databases using each method. It finds that semi-structured tools provide an alternative to structured tools, though each approach has advantages and disadvantages for certain types of queries.
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.
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.
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
This document discusses techniques for personalizing search engine results using concept-based user profiles. It proposes six methods for creating user profiles that capture both positive and negative user preferences and interests based on concepts extracted from search queries and results. The methods use machine learning algorithms to learn weighted concept vectors representing user profiles. An evaluation found that profiles capturing both positive and negative preferences performed best. The goal is to resolve query ambiguity and increase result relevance by understanding each user's unique interests and preferences.
A novel method for generating an elearning ontologyIJDKP
The Semantic Web provides a common framework that allows data to be shared and reused across
applications, enterprises, and community boundaries. The existing web applications need to express
semantics that can be extracted from users' navigation and content, in order to fulfill users' needs. Elearning
has specific requirements that can be satisfied through the extraction of semantics from learning
management systems (LMS) that use relational databases (RDB) as backend. In this paper, we propose
transformation rules for building owl ontology from the RDB of the open source LMS Moodle. It allows
transforming all possible cases in RDBs into ontological constructs. The proposed rules are enriched by
analyzing stored data to detect disjointness and totalness constraints in hierarchies, and calculating the
participation level of tables in n-ary relations. In addition, our technique is generic; hence it can be applied
to any RDB.
PERFORMANCE EVALUATION OF STRUCTURED AND SEMI-STRUCTURED BIOINFORMATICS TOOLS...ijseajournal
This document evaluates the performance of structured and semi-structured tools for accessing bioinformatics databases. It compares the Sequence Retrieval System (SRS) and Entrez search tools for structured data retrieval to Perl and BioPerl programs for semi-structured data retrieval. The study retrieves gene information from the European Bioinformatics Institute and National Centre for Biotechnology Information databases using each method. It finds that semi-structured tools provide an alternative to structured tools, though each approach has advantages and disadvantages for certain types of queries.
PERFORMANCE EVALUATION OF STRUCTURED AND SEMI-STRUCTURED BIOINFORMATICS TOOLS...ijseajournal
This document evaluates the performance of structured and semi-structured tools for accessing bioinformatics databases. It compares the Sequence Retrieval System (SRS) and Entrez search tools for structured data retrieval to Perl and BioPerl programs for semi-structured data retrieval. The study retrieves gene information from the European Bioinformatics Institute and National Center for Biotechnology Information databases using each method. It finds that semi-structured tools provide an alternative to structured tools, though each approach has advantages and disadvantages for certain types of queries.
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.
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.
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
This document discusses techniques for personalizing search engine results using concept-based user profiles. It proposes six methods for creating user profiles that capture both positive and negative user preferences and interests based on concepts extracted from search queries and results. The methods use machine learning algorithms to learn weighted concept vectors representing user profiles. An evaluation found that profiles capturing both positive and negative preferences performed best. The goal is to resolve query ambiguity and increase result relevance by understanding each user's unique interests and preferences.
A novel method for generating an elearning ontologyIJDKP
The Semantic Web provides a common framework that allows data to be shared and reused across
applications, enterprises, and community boundaries. The existing web applications need to express
semantics that can be extracted from users' navigation and content, in order to fulfill users' needs. Elearning
has specific requirements that can be satisfied through the extraction of semantics from learning
management systems (LMS) that use relational databases (RDB) as backend. In this paper, we propose
transformation rules for building owl ontology from the RDB of the open source LMS Moodle. It allows
transforming all possible cases in RDBs into ontological constructs. The proposed rules are enriched by
analyzing stored data to detect disjointness and totalness constraints in hierarchies, and calculating the
participation level of tables in n-ary relations. In addition, our technique is generic; hence it can be applied
to any RDB.
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.
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
Custom-Made Ranking in Databases Establishing and Utilizing an Appropriate Wo...ijsrd.com
Custom Rating System which provides a facility to the users, that they can search and download best articles or anything on the system in the database. The article or anything can be any text content which can describe a product, a book, an institution, an application, a company or anything. This system consists of two set of users, one is the normal user and another is the administrator. The users have to register and login to the system first, in order to use the system. The users have the following privileges. Write Article and Upload Relevant Files, Post Related URL to each article for other users reference, Search and Read Article posted by other users, Rate the articles posted by other users. The articles which are written by any user are sent to the Administrator for Approval. After approval of the articles by the administrator, they are available for the users to search and download. Based on the Description provided in an article, it can be searched by any registered user on the system. The user can see the article, download a file if available and the user can rate the article based on the article. Rating can be given in terms of 1 Star to 5 Star. The users can search the article. The list of articles displayed can be sorted based on following parameters: Rating, Popularity (Number of Clicks on the Article),Relevance (Based on number of matching keywords provided),All Articles uploaded by a specific user.
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.
COLLABORATIVE BIBLIOGRAPHIC SYSTEM FOR REVIEW/SURVEY ARTICLESijcsit
This paper proposes a Bibliographic system intends to exchange bibliographic information of survey/review articles by relying on Web service technology. It allows researchers and university students
to interact with system via single service using platform-independent standard named Web service to add,
search and retrieve bibliographic information of review articles in various science and technology fields
and build-up a dedicated database for these articles in each science and technology field. Additionally,
different implementation scenarios of the proposed system are presented and described, andrich features
that offered by such system are studied and described. However, this paper explains the proposed system
using computing area due to the existence of detailed taxonomy of this area, which allows defining the
system, their functionalities and features provided.However, the proposed system is not only confined to
computing area, it can support any other science and technology area without any need to modify this
system.
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.
QUERY EXPANSION WITH ENRICHED USER PROFILES FOR PERSONALIZED SEARCH UTILIZING...Prasadu Peddi
The document proposes two novel techniques for personalized query expansion using folksonomy data. It introduces a model that constructs enriched user profiles by integrating word embeddings with topic models from user annotations and an external corpus. The first technique selects expansion terms using topical weights-enhanced word embeddings. The second calculates topical relevance between the query and user profile terms. An evaluation shows the approaches outperform existing non-personalized and personalized query expansion methods.
An Efficient Hybrid Successive Markov Model for Predicting Web User Usage Beh...Waqas Tariq
With the continued growth and proliferation of Web services and Web based information systems, the volumes of user data have reached astronomical proportions. Analyzing such data using Web Usage Mining can help to determine the visiting interests or needs of the web user. As web log is incremental in nature, it becomes a crucial issue to predict exactly the ways how users browse websites. It is necessary for web miners to use predictive mining techniques to filter the unwanted categories for reducing the operational scope. The first-order Markov model has low accuracy in achieving right predictions, which is why extensions to higher order models are necessary. All higher order Markov model holds the promise of achieving higher prediction accuracies, improved coverage than any single-order Markov model but holds high state space complexity. Hence a Hybrid Markov Model is required to improve the operation performance and prediction accuracy significantly. The present paper introduces An Efficient Hybrid Successive Markov Prediction Model, HSMP. The HSMP model is initially predicts the possible wanted categories using Relevance factor, which can be used to infer the users’ browsing behavior between web categories. Then predict the pages in predicted categories using techniques for intelligently combining different order Markov models so that the resulting model has low state complexity, improved prediction accuracy and retains the coverage of the all higher order Markov model. These techniques eliminates low support states, evaluates the probability distribution and estimates the error associated with each state without affecting the overall accuracy as well as protection of the resulting model. To validate the proposed prediction model, several experiments were conducted and results proven this are claimed in this paper.
This document provides a listing and brief descriptions of working papers from 2000. It includes 12 papers with titles and short 1-2 paragraph summaries of each paper's topic or focus. The papers cover a range of topics related to text mining, machine learning, data compression, knowledge discovery, and user interfaces for developing classifiers.
Adaptive Search Based On User Tags in Social NetworkingIOSR Journals
This document summarizes an article about adaptive search based on user tags in social networking. It discusses using tags that users apply to images in social media sites like Flickr to improve image search and personalize results. It proposes using topic models to identify different meanings of ambiguous tags and a user's interests to display more relevant images. The framework involves reranking images based on aesthetics scores predicted from user comments, and using tag-based and group-based metadata to discover topics and personalize search results. Future work could further analyze community-generated metadata to identify interests and refine search algorithms.
This document discusses tag-based information retrieval using folksonomies. It describes how folksonomies allow for tag-based browsing and retrieval of user-generated content. Several algorithms for folksonomy-based information retrieval are summarized, including FolkRank, which adapts PageRank to folksonomies, and GFolkRank, which extends FolkRank to account for grouping of resources. The document also discusses personalized variants of these algorithms and evaluates their performance on real datasets.
This document discusses web page classification using a rule-based system. It begins by introducing the problem of classifying the large amount of unstructured information on the web. It then discusses various approaches to web page classification, including text content-based categorization and link and content analysis. The document focuses on using a rule-based classifier to assign HTML documents to predefined categories by checking for occurrences of system rules in the HTML content. Finally, it discusses common machine learning algorithms that have been used for web page classification, such as association rule mining, naive Bayes, support vector machines, logistic regression, and decision trees. The goal of the proposed system is to enhance other web page classification systems by enabling online classification of web pages.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Performance Evaluation of Query Processing Techniques in Information Retrievalidescitation
The first element of the search process is the query.
The user query being on an average restricted to two or three
keywords makes the query ambiguous to the search engine.
Given the user query, the goal of an Information Retrieval
[IR] system is to retrieve information which might be useful
or relevant to the information need of the user. Hence, the
query processing plays an important role in IR system.
The query processing can be divided into four categories
i.e. query expansion, query optimization, query classification and
query parsing. In this paper an attempt is made to evaluate the
performance of query processing algorithms in each of the
category. The evaluation was based on dataset as specified by
Forum for Information Retrieval [FIRE15]. The criteria used
for evaluation are precision and relative recall. The analysis is
based on the importance of each step in query processing. The
experimental results show that the significance of each step
in query processing and also the relevance of web semantics
and spelling correction in the user query.
This document summarizes an approach to improve personalized ranking using associated edge weights. The key points are:
1) Personalized ranking aims to improve traditional search and retrieval by tailoring results to a user's interests. Authority flow approaches like PageRank and ObjectRank can be used for personalized ranking on entity-relationship graphs.
2) Edge-based personalization assigns different weights to edge types based on the user, affecting authority flow. The paper focuses on improving edge-based personalization by hybridizing the ScaleRank algorithm with k-means clustering.
3) ScaleRank approximates the DataApprox algorithm for ranking. The hybrid approach uses k-means clustering on ScaleRank output to further group related nodes,
The authors develop a PubMed Central query to identify articles describing datasets deposited in the Gene Expression Omnibus database by training classifiers on open access articles and developing rules to express the query within PMC's interface. The query achieved a recall of 40% and precision of 94-65% depending on whether the articles were already linked in the database. The authors believe this approach could help curators identify missing links between datasets and primary citations.
Web Queries: From a Web of Data to a Semantic WebTim Furche
Keyword-based Web query languages are one significant effort towards combining the virtues of Web search, viz. being accessible to untrained users and able to cope with vastly heterogeneous data, with those of database-style Web queries. These languages operate essentially in the same setting as XQuery or SPARQL but with an interface for untrained users.
Keyword-based query languages trade some of the precision that languages like XQuery enable by allowing to formulate exactly what data to select and how to process it, for an easier interface accessible to untrained users. The yardstick for these languages becomes an easily accessible interface that does not sacrifice the essential premise of database-style Web queries, that selection and construction are precise enough to fully automate data processing tasks.
To ground the discussion of keyword-based query languages, we give a summary of what we perceive as the main contributions of research and development on Web query languages in the past decade. This summary focuses specifically on what sets Web query languages apart from their predecessors for databases.
Further, this tutorial (1) gives an overview over keyword-based query languages for XML and RDF (2) discusses where the existing approaches succeed and what, in our opinion, are the most glaring open issues, and (3) where, beyond keyword-based query languages, we see the need, the challenges, and the opportunities for combining the ease of use of Web search with the virtues of Web queries.
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.
Enhancing keyword search over relational databases using ontologiescsandit
Keyword Search Over Relational Databases (KSORDB) provides an easy way for casual users
to access relational databases using a set of keywords. Although much research has been done
and several prototypes have been developed recently, most of this research implements exact
(also called syntactic or keyword) match. So, if there is a vocabulary mismatch, the user cannot
get an answer although the database may contain relevant data. In this paper we propose a
system that overcomes this issue. Our system extends existing schema-free KSORDB systems
with semantic match features. So, if there were no or very few answers, our system exploits
domain ontology to progressively return related terms that can be used to retrieve more
relevant answers to user.
Determining Time of Queries for Re-ranking Search ResultsNattiya Kanhabua
Recent work on analyzing query logs shows that a significant fraction of queries are temporal, i.e., relevancy is dependent on time, and temporal queries play an important role in many domains, e.g., digital libraries and document archives. Temporal queries can be divided into two types: 1) those with temporal criteria explicitly provided by users, and 2) those with no temporal criteria provided. In this paper, we deal with the latter type of queries, i.e., queries that comprise only keywords, and their relevant documents are associated to particular time periods not given by the queries. We propose a number of methods to determine the time of queries using temporal language models. After that, we show how to increase the retrieval effectiveness by using the determined time of queries to re-rank the search results. Through extensive experiments we show that our proposed approaches improve retrieval effectiveness.
Sigir12 tutorial: Query Perfromance Prediction for IRDavid Carmel
This document summarizes a tutorial on query performance prediction given by Dr. David Carmel and Dr. Oren Kurland. It discusses the challenge of estimating query difficulty for information retrieval systems. Estimating query difficulty can provide benefits such as feedback to users, search engines, and system administrators. The tutorial covers basic concepts, query performance prediction methods, applications, and open challenges. It aims to help IR systems reduce variability in performance and better satisfy users' information needs.
This document summarizes a research paper on estimating skeletal maturity through the Tanner and Whitehouse bone age assessment method. The paper presents a system for segmenting wrist bones from left hand radiographs. The system first preprocesses images using Gaussian filtering and grayscale conversion. Canny edge detection is then used to extract regions of interest, which are classified using an Iterative Dichotomiser 3 classifier. The Tanner and Whitehouse method is applied to assess bone age. The system was tested on 50 images with 96% accuracy for males and 98% accuracy for females.
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.
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
Custom-Made Ranking in Databases Establishing and Utilizing an Appropriate Wo...ijsrd.com
Custom Rating System which provides a facility to the users, that they can search and download best articles or anything on the system in the database. The article or anything can be any text content which can describe a product, a book, an institution, an application, a company or anything. This system consists of two set of users, one is the normal user and another is the administrator. The users have to register and login to the system first, in order to use the system. The users have the following privileges. Write Article and Upload Relevant Files, Post Related URL to each article for other users reference, Search and Read Article posted by other users, Rate the articles posted by other users. The articles which are written by any user are sent to the Administrator for Approval. After approval of the articles by the administrator, they are available for the users to search and download. Based on the Description provided in an article, it can be searched by any registered user on the system. The user can see the article, download a file if available and the user can rate the article based on the article. Rating can be given in terms of 1 Star to 5 Star. The users can search the article. The list of articles displayed can be sorted based on following parameters: Rating, Popularity (Number of Clicks on the Article),Relevance (Based on number of matching keywords provided),All Articles uploaded by a specific user.
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.
COLLABORATIVE BIBLIOGRAPHIC SYSTEM FOR REVIEW/SURVEY ARTICLESijcsit
This paper proposes a Bibliographic system intends to exchange bibliographic information of survey/review articles by relying on Web service technology. It allows researchers and university students
to interact with system via single service using platform-independent standard named Web service to add,
search and retrieve bibliographic information of review articles in various science and technology fields
and build-up a dedicated database for these articles in each science and technology field. Additionally,
different implementation scenarios of the proposed system are presented and described, andrich features
that offered by such system are studied and described. However, this paper explains the proposed system
using computing area due to the existence of detailed taxonomy of this area, which allows defining the
system, their functionalities and features provided.However, the proposed system is not only confined to
computing area, it can support any other science and technology area without any need to modify this
system.
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.
QUERY EXPANSION WITH ENRICHED USER PROFILES FOR PERSONALIZED SEARCH UTILIZING...Prasadu Peddi
The document proposes two novel techniques for personalized query expansion using folksonomy data. It introduces a model that constructs enriched user profiles by integrating word embeddings with topic models from user annotations and an external corpus. The first technique selects expansion terms using topical weights-enhanced word embeddings. The second calculates topical relevance between the query and user profile terms. An evaluation shows the approaches outperform existing non-personalized and personalized query expansion methods.
An Efficient Hybrid Successive Markov Model for Predicting Web User Usage Beh...Waqas Tariq
With the continued growth and proliferation of Web services and Web based information systems, the volumes of user data have reached astronomical proportions. Analyzing such data using Web Usage Mining can help to determine the visiting interests or needs of the web user. As web log is incremental in nature, it becomes a crucial issue to predict exactly the ways how users browse websites. It is necessary for web miners to use predictive mining techniques to filter the unwanted categories for reducing the operational scope. The first-order Markov model has low accuracy in achieving right predictions, which is why extensions to higher order models are necessary. All higher order Markov model holds the promise of achieving higher prediction accuracies, improved coverage than any single-order Markov model but holds high state space complexity. Hence a Hybrid Markov Model is required to improve the operation performance and prediction accuracy significantly. The present paper introduces An Efficient Hybrid Successive Markov Prediction Model, HSMP. The HSMP model is initially predicts the possible wanted categories using Relevance factor, which can be used to infer the users’ browsing behavior between web categories. Then predict the pages in predicted categories using techniques for intelligently combining different order Markov models so that the resulting model has low state complexity, improved prediction accuracy and retains the coverage of the all higher order Markov model. These techniques eliminates low support states, evaluates the probability distribution and estimates the error associated with each state without affecting the overall accuracy as well as protection of the resulting model. To validate the proposed prediction model, several experiments were conducted and results proven this are claimed in this paper.
This document provides a listing and brief descriptions of working papers from 2000. It includes 12 papers with titles and short 1-2 paragraph summaries of each paper's topic or focus. The papers cover a range of topics related to text mining, machine learning, data compression, knowledge discovery, and user interfaces for developing classifiers.
Adaptive Search Based On User Tags in Social NetworkingIOSR Journals
This document summarizes an article about adaptive search based on user tags in social networking. It discusses using tags that users apply to images in social media sites like Flickr to improve image search and personalize results. It proposes using topic models to identify different meanings of ambiguous tags and a user's interests to display more relevant images. The framework involves reranking images based on aesthetics scores predicted from user comments, and using tag-based and group-based metadata to discover topics and personalize search results. Future work could further analyze community-generated metadata to identify interests and refine search algorithms.
This document discusses tag-based information retrieval using folksonomies. It describes how folksonomies allow for tag-based browsing and retrieval of user-generated content. Several algorithms for folksonomy-based information retrieval are summarized, including FolkRank, which adapts PageRank to folksonomies, and GFolkRank, which extends FolkRank to account for grouping of resources. The document also discusses personalized variants of these algorithms and evaluates their performance on real datasets.
This document discusses web page classification using a rule-based system. It begins by introducing the problem of classifying the large amount of unstructured information on the web. It then discusses various approaches to web page classification, including text content-based categorization and link and content analysis. The document focuses on using a rule-based classifier to assign HTML documents to predefined categories by checking for occurrences of system rules in the HTML content. Finally, it discusses common machine learning algorithms that have been used for web page classification, such as association rule mining, naive Bayes, support vector machines, logistic regression, and decision trees. The goal of the proposed system is to enhance other web page classification systems by enabling online classification of web pages.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Performance Evaluation of Query Processing Techniques in Information Retrievalidescitation
The first element of the search process is the query.
The user query being on an average restricted to two or three
keywords makes the query ambiguous to the search engine.
Given the user query, the goal of an Information Retrieval
[IR] system is to retrieve information which might be useful
or relevant to the information need of the user. Hence, the
query processing plays an important role in IR system.
The query processing can be divided into four categories
i.e. query expansion, query optimization, query classification and
query parsing. In this paper an attempt is made to evaluate the
performance of query processing algorithms in each of the
category. The evaluation was based on dataset as specified by
Forum for Information Retrieval [FIRE15]. The criteria used
for evaluation are precision and relative recall. The analysis is
based on the importance of each step in query processing. The
experimental results show that the significance of each step
in query processing and also the relevance of web semantics
and spelling correction in the user query.
This document summarizes an approach to improve personalized ranking using associated edge weights. The key points are:
1) Personalized ranking aims to improve traditional search and retrieval by tailoring results to a user's interests. Authority flow approaches like PageRank and ObjectRank can be used for personalized ranking on entity-relationship graphs.
2) Edge-based personalization assigns different weights to edge types based on the user, affecting authority flow. The paper focuses on improving edge-based personalization by hybridizing the ScaleRank algorithm with k-means clustering.
3) ScaleRank approximates the DataApprox algorithm for ranking. The hybrid approach uses k-means clustering on ScaleRank output to further group related nodes,
The authors develop a PubMed Central query to identify articles describing datasets deposited in the Gene Expression Omnibus database by training classifiers on open access articles and developing rules to express the query within PMC's interface. The query achieved a recall of 40% and precision of 94-65% depending on whether the articles were already linked in the database. The authors believe this approach could help curators identify missing links between datasets and primary citations.
Web Queries: From a Web of Data to a Semantic WebTim Furche
Keyword-based Web query languages are one significant effort towards combining the virtues of Web search, viz. being accessible to untrained users and able to cope with vastly heterogeneous data, with those of database-style Web queries. These languages operate essentially in the same setting as XQuery or SPARQL but with an interface for untrained users.
Keyword-based query languages trade some of the precision that languages like XQuery enable by allowing to formulate exactly what data to select and how to process it, for an easier interface accessible to untrained users. The yardstick for these languages becomes an easily accessible interface that does not sacrifice the essential premise of database-style Web queries, that selection and construction are precise enough to fully automate data processing tasks.
To ground the discussion of keyword-based query languages, we give a summary of what we perceive as the main contributions of research and development on Web query languages in the past decade. This summary focuses specifically on what sets Web query languages apart from their predecessors for databases.
Further, this tutorial (1) gives an overview over keyword-based query languages for XML and RDF (2) discusses where the existing approaches succeed and what, in our opinion, are the most glaring open issues, and (3) where, beyond keyword-based query languages, we see the need, the challenges, and the opportunities for combining the ease of use of Web search with the virtues of Web queries.
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.
Enhancing keyword search over relational databases using ontologiescsandit
Keyword Search Over Relational Databases (KSORDB) provides an easy way for casual users
to access relational databases using a set of keywords. Although much research has been done
and several prototypes have been developed recently, most of this research implements exact
(also called syntactic or keyword) match. So, if there is a vocabulary mismatch, the user cannot
get an answer although the database may contain relevant data. In this paper we propose a
system that overcomes this issue. Our system extends existing schema-free KSORDB systems
with semantic match features. So, if there were no or very few answers, our system exploits
domain ontology to progressively return related terms that can be used to retrieve more
relevant answers to user.
Determining Time of Queries for Re-ranking Search ResultsNattiya Kanhabua
Recent work on analyzing query logs shows that a significant fraction of queries are temporal, i.e., relevancy is dependent on time, and temporal queries play an important role in many domains, e.g., digital libraries and document archives. Temporal queries can be divided into two types: 1) those with temporal criteria explicitly provided by users, and 2) those with no temporal criteria provided. In this paper, we deal with the latter type of queries, i.e., queries that comprise only keywords, and their relevant documents are associated to particular time periods not given by the queries. We propose a number of methods to determine the time of queries using temporal language models. After that, we show how to increase the retrieval effectiveness by using the determined time of queries to re-rank the search results. Through extensive experiments we show that our proposed approaches improve retrieval effectiveness.
Sigir12 tutorial: Query Perfromance Prediction for IRDavid Carmel
This document summarizes a tutorial on query performance prediction given by Dr. David Carmel and Dr. Oren Kurland. It discusses the challenge of estimating query difficulty for information retrieval systems. Estimating query difficulty can provide benefits such as feedback to users, search engines, and system administrators. The tutorial covers basic concepts, query performance prediction methods, applications, and open challenges. It aims to help IR systems reduce variability in performance and better satisfy users' information needs.
This document summarizes a research paper on estimating skeletal maturity through the Tanner and Whitehouse bone age assessment method. The paper presents a system for segmenting wrist bones from left hand radiographs. The system first preprocesses images using Gaussian filtering and grayscale conversion. Canny edge detection is then used to extract regions of interest, which are classified using an Iterative Dichotomiser 3 classifier. The Tanner and Whitehouse method is applied to assess bone age. The system was tested on 50 images with 96% accuracy for males and 98% accuracy for females.
This document discusses keyword query routing to identify relevant data sources for keyword searches over multiple structured and linked data sources. It proposes using a multilevel inter-relationship graph and scoring mechanism to compute relevance and generate routing plans that route keywords only to pertinent sources. This improves keyword search performance without compromising result quality. An algorithm is developed based on modeling the search space and developing a summary model to incorporate relevance at different levels and dimensions. Experiments showed the summary model preserves relevant information compactly.
This document contains titles for projects from the years 2014-2015 related to IEEE and Java. It lists over 100 titles organized under categories such as mobile computing, cloud computing, data mining, networking, parallel and distributed systems and more. The titles describe technical research related to these areas, with a focus on security, privacy, efficiency and performance.
Effective and Efficient Entity Search in RDF dataRoi Blanco
Triple stores have long provided RDF storage as well as data access using expressive, formal query languages such as SPARQL. The new end users of the Semantic Web, however, are mostly unaware of SPARQL and overwhelmingly prefer imprecise, informal keyword queries for searching over data. At the same time, the amount of data on the Semantic Web is approaching the limits of the architectures that provide support for the full expressivity of SPARQL. These factors combined have led to an increased interest in semantic search, i.e. access to RDF data using Information Retrieval methods. In this work, we propose a method for effective and efficient entity search over RDF data. We describe an adaptation of the BM25F ranking function for RDF data, and demonstrate that it outperforms other state-of-the-art methods in ranking RDF resources. We also propose a set of new index structures for efficient retrieval and ranking of results. We implement these results using the open-source MG4J framework.
Introduction to question answering for linked data & big dataAndre Freitas
This document discusses question answering (QA) systems in the context of big data and heterogeneous data scenarios. It outlines the motivation and challenges for developing natural language interfaces for databases. The document covers the basic concepts and taxonomy of QA systems, including question types, answer types, data sources, and domains. It also discusses the anatomy and components of a typical QA system.
Effective Navigation of Query Results Based On HierarchiesAkhil Ambekar
This document discusses solutions to the problem of information overload when searching large biomedical databases like PubMed. It presents an interactive navigation model that categorizes search results according to the MeSH concept hierarchy. This allows users to efficiently explore search results by expanding nodes in the hierarchy and viewing citations attached to concepts. An evaluation shows that this navigation method outperforms static categorization approaches for returning relevant citations.
This document discusses a navigation cost modeling technique based on ontology for effective navigation of query results from large datasets. It presents an approach that uses concept hierarchies built from annotated data to categorize results and reduce the navigation cost for users. An initial navigation tree is constructed from the dataset ontology and refined by removing empty nodes. The tree is then dynamically expanded at certain points to minimize the user's navigation cost and quickly reach the desired results.
Navigation Cost Modeling Based On OntologyIOSR Journals
This document discusses a navigation cost modeling technique based on ontology for effective navigation of query results from large datasets. It presents an approach that uses concept hierarchies built from annotated data to categorize results and reduce the number displayed to users. An initial navigation tree is constructed from the concept hierarchies and optimized by removing empty nodes. EdgeCuts are then used to expand portions of the tree to minimize navigation cost for users. The proposed technique aims to provide more efficient navigation of query results than existing systems through categorization, ranking and modeling of navigation costs.
LigerCat is a web application that allows users to search the PubMed database for articles using keywords or DNA/protein sequences. It displays the search results as a tag cloud of associated MeSH descriptors weighted by frequency, and as a publication timeline graph. Users can explore subsets of articles by selecting terms from the cloud. LigerCat integrates local databases with NLM resources to provide precompiled queries and dynamically update results. It uses a scalable architecture with load balancing, queues, and Redis to improve processing speeds.
The document introduces three tools - GoPubMed, MEDSUM, and Quertle - that provide alternative interfaces for PubMed to help researchers more easily search, retrieve, analyze, and visualize biomedical literature beyond what is available through the standard PubMed interface by offering features like result filtering, statistics, and semantic searching. These tools aim to address some of the limitations of PubMed like difficulty with link resolvers, unranked results, and lack of analysis capabilities.
Open domain question answering system using semantic role labelingeSAT Publishing House
1. The document describes a proposed open domain question answering system that uses semantic role labeling to extract answers from documents retrieved from the web.
2. The system consists of three modules: question processing, document retrieval, and answer extraction. Semantic role labeling is used in the answer extraction module to identify answers based on the question type.
3. An evaluation of the proposed system showed it achieved higher accuracy compared to a baseline system using only pattern matching for answer extraction.
Biomedical indexing and retrieval system based on language modeling approachijseajournal
This summarizes a research paper that proposes a biomedical indexing and retrieval system called BIOINSY. It uses a language modeling approach to select the best Medical Subject Headings (MeSH) descriptors to index medical articles from sources like PUBMED. The system first preprocesses articles by splitting text, stemming words, and removing stop words. It then extracts terms using a hybrid linguistic and statistical approach. Terms are weighted based on semantic relationships in MeSH, not just statistics. Descriptors are selected by disambiguating terms and estimating the probability a descriptor was generated by the article's language model. Experiments showed the effectiveness of this conceptual indexing approach.
A scalable hybrid research paper recommender system for microaman341480
This document summarizes a hybrid recommender system used by Microsoft Academic to provide recommendations for over 160 million research papers. The system combines co-citation based recommendations, which analyze citation networks, and content based recommendations, which analyze paper metadata like titles and abstracts. It generates paper embeddings from text and clusters them to improve scalability. The recommendations are evaluated through a user study and made publicly available to facilitate further research.
TWO LEVEL SELF-SUPERVISED RELATION EXTRACTION FROM MEDLINE USING UMLSIJDKP
The biomedical research literature is one among many other domains that hides a precious knowledge, and
the biomedical community made an extensive use of this scientific literature to discover the facts of
biomedical entities, such as disease, drugs,etc.MEDLINE is a huge database of biomedical research
papers which remain a significantly underutilized source of biological information. Discovering the useful
knowledge from such huge corpus leads to various problems related to the type of information such as the
concepts related to the domain of texts and the semantic relationship associated with them. In this paper,
we propose a Two-level model for Self-supervised relation extraction from MEDLINE using Unified
Medical Language System (UMLS) Knowledge base. The model uses a Self-supervised Approach for
Relation Extraction (RE) by constructing enhanced training examples using information from UMLS. The
model shows a better result in comparison with current state of the art and naïve approaches
There are many characteristics of biological data. All these characteristics make the management of biological information a particularly challenging problem. Here mainly we will focus on characteristics of biological information and multidisciplinary field called bioinformatics. Bioinformatics, now a days has emerged with graduate degree programs in several universities.
Search Interface Feature Evaluation in BiosciencesZanda Mark
Read more here: http://pingar.com/
This paper reports findings on desirable interface features for different
search tasks in the biomedical domain. We conducted a user study where
we asked bioscientists to evaluate the usefulness of autocomplete, query
expansions, faceted refinement, related searches and results preview
implementations in new pilot interfaces and publicly available systems
while using baseline and their own queries. Our evaluation reveals that
there is a preference for certain features depending on the search task.
In addition, we touch on the current pain point of faceted search: the
acquisition of faceted subject metadata for unstructured documents.
We found a strong preference for prototypes displaying just a few facets
generated based on either the query or the matching documents.
Our evaluation reveals that there is a preference for certain features depending on the search task. In addition, we touch on the current pain point of faceted search: the acquisition of faceted subject metadata for unstructured documents. We found a strong preference for prototypes displaying just a few facets generated based on either the query or the matching documents.
A consistent and efficient graphical User Interface Design and Querying Organ...CSCJournals
We propose a software layer called GUEDOS-DB upon Object-Relational Database Management System ORDMS. In this work we apply it in Molecular Biology, more precisely Organelle complete genome. We aim to offer biologists the possibility to access in a unified way information spread among heterogeneous genome databanks. In this paper, the goal is firstly, to provide a visual schema graph through a number of illustrative examples. The adopted, human-computer interaction technique in this visual designing and querying makes very easy for biologists to formulate database queries compared with linear textual query representation.
Semantic Search of E-Learning Documents Using Ontology Based Systemijcnes
The keyword searching mechanism is traditionally used for information retrieval from Web based systems. However, this system fails to meet the requirements in Web searching of the expert knowledge base based on the popular semantic systems. Semantic search of E-learning documents based on ontology is increasingly adopted in information retrieval systems. Ontology based system simplifies the task of finding correct information on the Web by building a search system based on the meaning of keyword instead of the keyword itself. The major function of the ontology based system is the development of specification of conceptualization which enhances the connection between the information present in the Web pages with that of the background knowledge.The semantic gap existing between the keyword found in documents and those in query can be matched suitably using Ontology based system. This paper provides a detailed account of the semantic search of E-learning documents using ontology based system by making comparison between various ontology systems. Based on this comparison, this survey attempts to identify the possible directions for future research.
An Improved Annotation Based Summary Generation For Unstructured DataMelinda Watson
This document discusses annotation-based summarization of unstructured data. It begins with an introduction to annotation and information retrieval. Current annotation processes cannot maintain modifications due to frequent document updates. The document then reviews literature on automatic text classification, applying annotations to linked open data sets, and using domain ontologies for automatic document annotation. Keywords, sentences and contexts are extracted from documents for annotation. Different annotation models are discussed. The goal is to develop an improved annotation approach for summarizing unstructured data that can handle frequent document changes.
Clustering of medline documents using semi supervised spectral clusteringeSAT Publishing House
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
Clustering of medline documents using semi supervised spectral clusteringeSAT Journals
Abstract We are considering: local-content (LC) information, global-content (GC) information from PubMed and MESH (medical subject heading-MS) for the clustering of bio-medical documents. The performances of MEDLINE document clustering are enhanced from previous methods by combining both the LC and GC. We propose a semi-supervised spectral clustering method to overcome the limitations of representation space of earlier methods. Keywords- document clustering, semi-supervised clustering, spectral clustering
This document provides summaries of 12 working papers from 2000. The summaries are:
1. The paper discusses using compression models to identify acronyms in text.
2. The paper examines using compression models for text categorization to assign texts to predefined categories.
3. The paper is reserved for Sally Jo.
4. The paper explores letting users build classifiers through interactive machine learning.
That's a concise 3 sentence summary of the document that highlights the key information about 4 of the 12 working papers it describes.
This document provides a listing and brief descriptions of working papers from 2000. It includes 12 papers with titles and short 1-2 paragraph summaries of each paper's topic or focus. The papers cover a range of topics related to text mining, machine learning, data compression, knowledge discovery, and user interfaces for developing classifiers.
This document discusses techniques for detecting duplicate records from multiple web databases. It begins with an abstract describing an unsupervised approach that uses classifiers like the weighted component similarity summing classifier and support vector machine along with a Gaussian mixture model to iteratively identify duplicate records. The document then provides details on related work, including probabilistic matching models, supervised and unsupervised learning techniques, distance-based techniques, rule-based approaches, and methods for improving efficiency like blocking and the sorted neighborhood approach.
Similar to IJERD(www.ijerd.com)International Journal of Engineering Research and Development (20)
A Novel Method for Prevention of Bandwidth Distributed Denial of Service AttacksIJERD Editor
Distributed Denial of Service (DDoS) Attacks became a massive threat to the Internet. Traditional
Architecture of internet is vulnerable to the attacks like DDoS. Attacker primarily acquire his army of Zombies,
then that army will be instructed by the Attacker that when to start an attack and on whom the attack should be
done. In this paper, different techniques which are used to perform DDoS Attacks, Tools that were used to
perform Attacks and Countermeasures in order to detect the attackers and eliminate the Bandwidth Distributed
Denial of Service attacks (B-DDoS) are reviewed. DDoS Attacks were done by using various Flooding
techniques which are used in DDoS attack.
The main purpose of this paper is to design an architecture which can reduce the Bandwidth
Distributed Denial of service Attack and make the victim site or server available for the normal users by
eliminating the zombie machines. Our Primary focus of this paper is to dispute how normal machines are
turning into zombies (Bots), how attack is been initiated, DDoS attack procedure and how an organization can
save their server from being a DDoS victim. In order to present this we implemented a simulated environment
with Cisco switches, Routers, Firewall, some virtual machines and some Attack tools to display a real DDoS
attack. By using Time scheduling, Resource Limiting, System log, Access Control List and some Modular
policy Framework we stopped the attack and identified the Attacker (Bot) machines
Hearing loss is one of the most common human impairments. It is estimated that by year 2015 more
than 700 million people will suffer mild deafness. Most can be helped by hearing aid devices depending on the
severity of their hearing loss. This paper describes the implementation and characterization details of a dual
channel transmitter front end (TFE) for digital hearing aid (DHA) applications that use novel micro
electromechanical- systems (MEMS) audio transducers and ultra-low power-scalable analog-to-digital
converters (ADCs), which enable a very-low form factor, energy-efficient implementation for next-generation
DHA. The contribution of the design is the implementation of the dual channel MEMS microphones and powerscalable
ADC system.
Influence of tensile behaviour of slab on the structural Behaviour of shear c...IJERD Editor
-A composite beam is composed of a steel beam and a slab connected by means of shear connectors
like studs installed on the top flange of the steel beam to form a structure behaving monolithically. This study
analyzes the effects of the tensile behavior of the slab on the structural behavior of the shear connection like slip
stiffness and maximum shear force in composite beams subjected to hogging moment. The results show that the
shear studs located in the crack-concentration zones due to large hogging moments sustain significantly smaller
shear force and slip stiffness than the other zones. Moreover, the reduction of the slip stiffness in the shear
connection appears also to be closely related to the change in the tensile strain of rebar according to the increase
of the load. Further experimental and analytical studies shall be conducted considering variables such as the
reinforcement ratio and the arrangement of shear connectors to achieve efficient design of the shear connection
in composite beams subjected to hogging moment.
Gold prospecting using Remote Sensing ‘A case study of Sudan’IJERD Editor
Gold has been extracted from northeast Africa for more than 5000 years, and this may be the first
place where the metal was extracted. The Arabian-Nubian Shield (ANS) is an exposure of Precambrian
crystalline rocks on the flanks of the Red Sea. The crystalline rocks are mostly Neoproterozoic in age. ANS
includes the nations of Israel, Jordan. Egypt, Saudi Arabia, Sudan, Eritrea, Ethiopia, Yemen, and Somalia.
Arabian Nubian Shield Consists of juvenile continental crest that formed between 900 550 Ma, when intra
oceanic arc welded together along ophiolite decorated arc. Primary Au mineralization probably developed in
association with the growth of intra oceanic arc and evolution of back arc. Multiple episodes of deformation
have obscured the primary metallogenic setting, but at least some of the deposits preserve evidence that they
originate as sea floor massive sulphide deposits.
The Red Sea Hills Region is a vast span of rugged, harsh and inhospitable sector of the Earth with
inimical moon-like terrain, nevertheless since ancient times it is famed to be an abode of gold and was a major
source of wealth for the Pharaohs of ancient Egypt. The Pharaohs old workings have been periodically
rediscovered through time. Recent endeavours by the Geological Research Authority of Sudan led to the
discovery of a score of occurrences with gold and massive sulphide mineralizations. In the nineties of the
previous century the Geological Research Authority of Sudan (GRAS) in cooperation with BRGM utilized
satellite data of Landsat TM using spectral ratio technique to map possible mineralized zones in the Red Sea
Hills of Sudan. The outcome of the study mapped a gossan type gold mineralization. Band ratio technique was
applied to Arbaat area and a signature of alteration zone was detected. The alteration zones are commonly
associated with mineralization. The alteration zones are commonly associated with mineralization. A filed check
confirmed the existence of stock work of gold bearing quartz in the alteration zone. Another type of gold
mineralization that was discovered using remote sensing is the gold associated with metachert in the Atmur
Desert.
Reducing Corrosion Rate by Welding DesignIJERD Editor
This document summarizes a study on reducing corrosion rates in steel through welding design. The researchers tested different welding groove designs (X, V, 1/2X, 1/2V) and preheating temperatures (400°C, 500°C, 600°C) on ferritic malleable iron samples. Testing found that X and V groove designs with 500°C and 600°C preheating had corrosion rates of 0.5-0.69% weight loss after 14 days, compared to 0.57-0.76% for 400°C preheating. Higher preheating reduced residual stresses which decreased corrosion. Residual stresses were 1.7 MPa for optimal X groove and 600°C
Router 1X3 – RTL Design and VerificationIJERD Editor
Routing is the process of moving a packet of data from source to destination and enables messages
to pass from one computer to another and eventually reach the target machine. A router is a networking device
that forwards data packets between computer networks. It is connected to two or more data lines from different
networks (as opposed to a network switch, which connects data lines from one single network). This paper,
mainly emphasizes upon the study of router device, it‟s top level architecture, and how various sub-modules of
router i.e. Register, FIFO, FSM and Synchronizer are synthesized, and simulated and finally connected to its top
module.
Active Power Exchange in Distributed Power-Flow Controller (DPFC) At Third Ha...IJERD Editor
This paper presents a component within the flexible ac-transmission system (FACTS) family, called
distributed power-flow controller (DPFC). The DPFC is derived from the unified power-flow controller (UPFC)
with an eliminated common dc link. The DPFC has the same control capabilities as the UPFC, which comprise
the adjustment of the line impedance, the transmission angle, and the bus voltage. The active power exchange
between the shunt and series converters, which is through the common dc link in the UPFC, is now through the
transmission lines at the third-harmonic frequency. DPFC multiple small-size single-phase converters which
reduces the cost of equipment, no voltage isolation between phases, increases redundancy and there by
reliability increases. The principle and analysis of the DPFC are presented in this paper and the corresponding
simulation results that are carried out on a scaled prototype are also shown.
Mitigation of Voltage Sag/Swell with Fuzzy Control Reduced Rating DVRIJERD Editor
Power quality has been an issue that is becoming increasingly pivotal in industrial electricity
consumers point of view in recent times. Modern industries employ Sensitive power electronic equipments,
control devices and non-linear loads as part of automated processes to increase energy efficiency and
productivity. Voltage disturbances are the most common power quality problem due to this the use of a large
numbers of sophisticated and sensitive electronic equipment in industrial systems is increased. This paper
discusses the design and simulation of dynamic voltage restorer for improvement of power quality and
reduce the harmonics distortion of sensitive loads. Power quality problem is occurring at non-standard
voltage, current and frequency. Electronic devices are very sensitive loads. In power system voltage sag,
swell, flicker and harmonics are some of the problem to the sensitive load. The compensation capability
of a DVR depends primarily on the maximum voltage injection ability and the amount of stored
energy available within the restorer. This device is connected in series with the distribution feeder at
medium voltage. A fuzzy logic control is used to produce the gate pulses for control circuit of DVR and the
circuit is simulated by using MATLAB/SIMULINK software.
Study on the Fused Deposition Modelling In Additive ManufacturingIJERD Editor
Additive manufacturing process, also popularly known as 3-D printing, is a process where a product
is created in a succession of layers. It is based on a novel materials incremental manufacturing philosophy.
Unlike conventional manufacturing processes where material is removed from a given work price to derive the
final shape of a product, 3-D printing develops the product from scratch thus obviating the necessity to cut away
materials. This prevents wastage of raw materials. Commonly used raw materials for the process are ABS
plastic, PLA and nylon. Recently the use of gold, bronze and wood has also been implemented. The complexity
factor of this process is 0% as in any object of any shape and size can be manufactured.
Spyware triggering system by particular string valueIJERD Editor
This computer programme can be used for good and bad purpose in hacking or in any general
purpose. We can say it is next step for hacking techniques such as keylogger and spyware. Once in this system if
user or hacker store particular string as a input after that software continually compare typing activity of user
with that stored string and if it is match then launch spyware programme.
A Blind Steganalysis on JPEG Gray Level Image Based on Statistical Features a...IJERD Editor
This paper presents a blind steganalysis technique to effectively attack the JPEG steganographic
schemes i.e. Jsteg, F5, Outguess and DWT Based. The proposed method exploits the correlations between
block-DCTcoefficients from intra-block and inter-block relation and the statistical moments of characteristic
functions of the test image is selected as features. The features are extracted from the BDCT JPEG 2-array.
Support Vector Machine with cross-validation is implemented for the classification.The proposed scheme gives
improved outcome in attacking.
Secure Image Transmission for Cloud Storage System Using Hybrid SchemeIJERD Editor
- Data over the cloud is transferred or transmitted between servers and users. Privacy of that
data is very important as it belongs to personal information. If data get hacked by the hacker, can be
used to defame a person’s social data. Sometimes delay are held during data transmission. i.e. Mobile
communication, bandwidth is low. Hence compression algorithms are proposed for fast and efficient
transmission, encryption is used for security purposes and blurring is used by providing additional
layers of security. These algorithms are hybridized for having a robust and efficient security and
transmission over cloud storage system.
Application of Buckley-Leverett Equation in Modeling the Radius of Invasion i...IJERD Editor
A thorough review of existing literature indicates that the Buckley-Leverett equation only analyzes
waterflood practices directly without any adjustments on real reservoir scenarios. By doing so, quite a number
of errors are introduced into these analyses. Also, for most waterflood scenarios, a radial investigation is more
appropriate than a simplified linear system. This study investigates the adoption of the Buckley-Leverett
equation to estimate the radius invasion of the displacing fluid during waterflooding. The model is also adopted
for a Microbial flood and a comparative analysis is conducted for both waterflooding and microbial flooding.
Results shown from the analysis doesn’t only records a success in determining the radial distance of the leading
edge of water during the flooding process, but also gives a clearer understanding of the applicability of
microbes to enhance oil production through in-situ production of bio-products like bio surfactans, biogenic
gases, bio acids etc.
Gesture Gaming on the World Wide Web Using an Ordinary Web CameraIJERD Editor
- Gesture gaming is a method by which users having a laptop/pc/x-box play games using natural or
bodily gestures. This paper presents a way of playing free flash games on the internet using an ordinary webcam
with the help of open source technologies. Emphasis in human activity recognition is given on the pose
estimation and the consistency in the pose of the player. These are estimated with the help of an ordinary web
camera having different resolutions from VGA to 20mps. Our work involved giving a 10 second documentary to
the user on how to play a particular game using gestures and what are the various kinds of gestures that can be
performed in front of the system. The initial inputs of the RGB values for the gesture component is obtained by
instructing the user to place his component in a red box in about 10 seconds after the short documentary before
the game is finished. Later the system opens the concerned game on the internet on popular flash game sites like
miniclip, games arcade, GameStop etc and loads the game clicking at various places and brings the state to a
place where the user is to perform only gestures to start playing the game. At any point of time the user can call
off the game by hitting the esc key and the program will release all of the controls and return to the desktop. It
was noted that the results obtained using an ordinary webcam matched that of the Kinect and the users could
relive the gaming experience of the free flash games on the net. Therefore effective in game advertising could
also be achieved thus resulting in a disruptive growth to the advertising firms.
Hardware Analysis of Resonant Frequency Converter Using Isolated Circuits And...IJERD Editor
-LLC resonant frequency converter is basically a combo of series as well as parallel resonant ckt. For
LCC resonant converter it is associated with a disadvantage that, though it has two resonant frequencies, the
lower resonant frequency is in ZCS region[5]. For this application, we are not able to design the converter
working at this resonant frequency. LLC resonant converter existed for a very long time but because of
unknown characteristic of this converter it was used as a series resonant converter with basically a passive
(resistive) load. . Here, it was designed to operate in switching frequency higher than resonant frequency of the
series resonant tank of Lr and Cr converter acts very similar to Series Resonant Converter. The benefit of LLC
resonant converter is narrow switching frequency range with light load[6] . Basically, the control ckt plays a
very imp. role and hence 555 Timer used here provides a perfect square wave as the control ckt provides no
slew rate which makes the square wave really strong and impenetrable. The dead band circuit provides the
exclusive dead band in micro seconds so as to avoid the simultaneous firing of two pairs of IGBT’s where one
pair switches off and the other on for a slightest period of time. Hence, the isolator ckt here is associated with
each and every ckt used because it acts as a driver and an isolation to each of the IGBT is provided with one
exclusive transformer supply[3]. The IGBT’s are fired using the appropriate signal using the previous boards
and hence at last a high frequency rectifier ckt with a filtering capacitor is used to get an exact dc
waveform .The basic goal of this particular analysis is to observe the wave forms and characteristics of
converters with differently positioned passive elements in the form of tank circuits.
Simulated Analysis of Resonant Frequency Converter Using Different Tank Circu...IJERD Editor
LLC resonant frequency converter is basically a combo of series as well as parallel resonant ckt. For
LCC resonant converter it is associated with a disadvantage that, though it has two resonant frequencies, the
lower resonant frequency is in ZCS region [5]. For this application, we are not able to design the converter
working at this resonant frequency. LLC resonant converter existed for a very long time but because of
unknown characteristic of this converter it was used as a series resonant converter with basically a passive
(resistive) load. . Here, it was designed to operate in switching frequency higher than resonant frequency of the
series resonant tank of Lr and Cr converter acts very similar to Series Resonant Converter. The benefit of LLC
resonant converter is narrow switching frequency range with light load[6] . Basically, the control ckt plays a
very imp. role and hence 555 Timer used here provides a perfect square wave as the control ckt provides no
slew rate which makes the square wave really strong and impenetrable. The dead band circuit provides the
exclusive dead band in micro seconds so as to avoid the simultaneous firing of two pairs of IGBT’s where one
pair switches off and the other on for a slightest period of time. Hence, the isolator ckt here is associated with
each and every ckt used because it acts as a driver and an isolation to each of the IGBT is provided with one
exclusive transformer supply[3]. The IGBT’s are fired using the appropriate signal using the previous boards
and hence at last a high frequency rectifier ckt with a filtering capacitor is used to get an exact dc
waveform .The basic goal of this particular analysis is to observe the wave forms and characteristics of
converters with differently positioned passive elements in the form of tank circuits. The supported simulation
is done through PSIM 6.0 software tool
Amateurs Radio operator, also known as HAM communicates with other HAMs through Radio
waves. Wireless communication in which Moon is used as natural satellite is called Moon-bounce or EME
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operated amateur HAM radio was difficult. Even with the modest setup having good transceiver, power
amplifier and high gain antenna with high directivity, VHF DXing is possible. Generally 2X11 YAGI antenna
along with rotor to set horizontal and vertical angle is used. Moon tracking software gives exact location,
visibility of Moon at both the stations and other vital data to acquire real time position of moon.
“MS-Extractor: An Innovative Approach to Extract Microsatellites on „Y‟ Chrom...IJERD Editor
Simple Sequence Repeats (SSR), also known as Microsatellites, have been extensively used as
molecular markers due to their abundance and high degree of polymorphism. The nucleotide sequences of
polymorphic forms of the same gene should be 99.9% identical. So, Microsatellites extraction from the Gene is
crucial. However, Microsatellites repeat count is compared, if they differ largely, he has some disorder. The Y
chromosome likely contains 50 to 60 genes that provide instructions for making proteins. Because only males
have the Y chromosome, the genes on this chromosome tend to be involved in male sex determination and
development. Several Microsatellite Extractors exist and they fail to extract microsatellites on large data sets of
giga bytes and tera bytes in size. The proposed tool “MS-Extractor: An Innovative Approach to extract
Microsatellites on „Y‟ Chromosome” can extract both Perfect as well as Imperfect Microsatellites from large
data sets of human genome „Y‟. The proposed system uses string matching with sliding window approach to
locate Microsatellites and extracts them.
Importance of Measurements in Smart GridIJERD Editor
- The need to get reliable supply, independence from fossil fuels, and capability to provide clean
energy at a fixed and lower cost, the existing power grid structure is transforming into Smart Grid. The
development of a smart energy distribution grid is a current goal of many nations. A Smart Grid should have
new capabilities such as self-healing, high reliability, energy management, and real-time pricing. This new era
of smart future grid will lead to major changes in existing technologies at generation, transmission and
distribution levels. The incorporation of renewable energy resources and distribution generators in the existing
grid will increase the complexity, optimization problems and instability of the system. This will lead to a
paradigm shift in the instrumentation and control requirements for Smart Grids for high quality, stable and
reliable electricity supply of power. The monitoring of the grid system state and stability relies on the
availability of reliable measurement of data. In this paper the measurement areas that highlight new
measurement challenges, development of the Smart Meters and the critical parameters of electric energy to be
monitored for improving the reliability of power systems has been discussed.
Study of Macro level Properties of SCC using GGBS and Lime stone powderIJERD Editor
The document summarizes a study on the use of ground granulated blast furnace slag (GGBS) and limestone powder to replace cement in self-compacting concrete (SCC). Tests were conducted on SCC mixes with 0-50% replacement of cement with GGBS and 0-20% replacement with limestone powder. The results showed that replacing 30% of cement with GGBS and 15% with limestone powder produced SCC with the highest compressive strength of 46MPa, meeting fresh property requirements. The study concluded that this ternary blend of cement, GGBS and limestone powder can improve SCC properties while reducing costs.
8 Surprising Reasons To Meditate 40 Minutes A Day That Can Change Your Life.pptxHolistified Wellness
We’re talking about Vedic Meditation, a form of meditation that has been around for at least 5,000 years. Back then, the people who lived in the Indus Valley, now known as India and Pakistan, practised meditation as a fundamental part of daily life. This knowledge that has given us yoga and Ayurveda, was known as Veda, hence the name Vedic. And though there are some written records, the practice has been passed down verbally from generation to generation.
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The UK is currently facing a Adhd Medication Shortage Uk, which has left many patients and their families grappling with uncertainty and frustration. ADHD, or Attention Deficit Hyperactivity Disorder, is a chronic condition that requires consistent medication to manage effectively. This shortage has highlighted the critical role these medications play in the daily lives of those affected by ADHD. Contact : +1 (747) 209 – 3649 E-mail : sales@trinexpharmacy.com
Cell Therapy Expansion and Challenges in Autoimmune DiseaseHealth Advances
There is increasing confidence that cell therapies will soon play a role in the treatment of autoimmune disorders, but the extent of this impact remains to be seen. Early readouts on autologous CAR-Ts in lupus are encouraging, but manufacturing and cost limitations are likely to restrict access to highly refractory patients. Allogeneic CAR-Ts have the potential to broaden access to earlier lines of treatment due to their inherent cost benefits, however they will need to demonstrate comparable or improved efficacy to established modalities.
In addition to infrastructure and capacity constraints, CAR-Ts face a very different risk-benefit dynamic in autoimmune compared to oncology, highlighting the need for tolerable therapies with low adverse event risk. CAR-NK and Treg-based therapies are also being developed in certain autoimmune disorders and may demonstrate favorable safety profiles. Several novel non-cell therapies such as bispecific antibodies, nanobodies, and RNAi drugs, may also offer future alternative competitive solutions with variable value propositions.
Widespread adoption of cell therapies will not only require strong efficacy and safety data, but also adapted pricing and access strategies. At oncology-based price points, CAR-Ts are unlikely to achieve broad market access in autoimmune disorders, with eligible patient populations that are potentially orders of magnitude greater than the number of currently addressable cancer patients. Developers have made strides towards reducing cell therapy COGS while improving manufacturing efficiency, but payors will inevitably restrict access until more sustainable pricing is achieved.
Despite these headwinds, industry leaders and investors remain confident that cell therapies are poised to address significant unmet need in patients suffering from autoimmune disorders. However, the extent of this impact on the treatment landscape remains to be seen, as the industry rapidly approaches an inflection point.
These lecture slides, by Dr Sidra Arshad, offer a simplified look into the mechanisms involved in the regulation of respiration:
Learning objectives:
1. Describe the organisation of respiratory center
2. Describe the nervous control of inspiration and respiratory rhythm
3. Describe the functions of the dorsal and respiratory groups of neurons
4. Describe the influences of the Pneumotaxic and Apneustic centers
5. Explain the role of Hering-Breur inflation reflex in regulation of inspiration
6. Explain the role of central chemoreceptors in regulation of respiration
7. Explain the role of peripheral chemoreceptors in regulation of respiration
8. Explain the regulation of respiration during exercise
9. Integrate the respiratory regulatory mechanisms
10. Describe the Cheyne-Stokes breathing
Study Resources:
1. Chapter 42, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 36, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 13, Human Physiology by Lauralee Sherwood, 9th edition
share - Lions, tigers, AI and health misinformation, oh my!.pptxTina Purnat
• Pitfalls and pivots needed to use AI effectively in public health
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Local Advanced Lung Cancer: Artificial Intelligence, Synergetics, Complex Sys...Oleg Kshivets
Overall life span (LS) was 1671.7±1721.6 days and cumulative 5YS reached 62.4%, 10 years – 50.4%, 20 years – 44.6%. 94 LCP lived more than 5 years without cancer (LS=2958.6±1723.6 days), 22 – more than 10 years (LS=5571±1841.8 days). 67 LCP died because of LC (LS=471.9±344 days). AT significantly improved 5YS (68% vs. 53.7%) (P=0.028 by log-rank test). Cox modeling displayed that 5YS of LCP significantly depended on: N0-N12, T3-4, blood cell circuit, cell ratio factors (ratio between cancer cells-CC and blood cells subpopulations), LC cell dynamics, recalcification time, heparin tolerance, prothrombin index, protein, AT, procedure type (P=0.000-0.031). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and N0-12 (rank=1), thrombocytes/CC (rank=2), segmented neutrophils/CC (3), eosinophils/CC (4), erythrocytes/CC (5), healthy cells/CC (6), lymphocytes/CC (7), stick neutrophils/CC (8), leucocytes/CC (9), monocytes/CC (10). Correct prediction of 5YS was 100% by neural networks computing (error=0.000; area under ROC curve=1.0).
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IJERD(www.ijerd.com)International Journal of Engineering Research and Development
1. International Journal of Engineering Research and Development
ISSN: 2278-067X, Volume 2, Issue 1 (July 2012), PP. 01-06
www.ijerd.com
Efficient Navigation of Query Results Using Concept Hierarchies
Shilpa Mentada1, B. Govinda Lakshmi2
1
2/2 M.TECH SE, Department of CSE, Sri Sivani College of Engineering, Chilakapalem, Srikakulam, AP, India
2
Associate Professor, Department of CSE, Sri Sivani College of Engineering, Chilakapalem, Srikakulam, AP, India
Abstract—with the dramatically quick and explosive growth of information available over the Internet, World Wide Web
has become a powerful platform to store, disseminate and retrieve information as well as mine useful knowledge. Due to
the properties of the huge, diverse, dynamic and unstructured nature of Web data, Web data research has encountered a
lot of challenges. To overcome this so many researchers proposed various techniques but still there is a requirement. To
fulfill this, in this paper we demonstrate the BioNav system, a novel search interface for biomedical databases, such as
PubMed. BioNav enables users to navigate large number of query results by categorizing them using MeSH; a
comprehensive concept hierarchy used by PubMed. Once the query results are organized into a navigation tree, BioNav
reveals only a small subset of the concept nodes at each step, selected such that the expected user navigation cost is
minimized.
Keywords––Web Mining, World wide web, Web Personalization, BioNav System, MeSH;
I. INTRODUCTION
The last decade has been marked by unprecedented growth in both the production of biomedical data and the
amount of published literature discussing it. The MEDLINE database, on which the PubMed search engine operates,
contains over 18 million citations, and the database is growing at the rate of 500,000 new citations each year [1-3]. Keyword
search queries on these databases return a large results set from which only a small portion is relevant for the user. Many
solutions have been proposed to address this problem – commonly referred to as information-overload [3-6]. These
approaches can be broadly classified into two classes: ranking and categorization, which can also be combined. BioNav
belongs primarily to the categorization class, which is ideal for this domain given the rich concept hierarchies available for
biomedical data, such as MeSH. Each citation in MEDLINE is associated with several MeSH concepts in two ways: (i) by
being explicitly annotated with them, and (ii) by mentioning them in their text. Since these associations are provided by
PubMed, a relatively straightforward interface to navigate the query result would first attach the citations to the
corresponding MeSH concept nodes and then let the user navigate the concept hierarchy
Figure 1. Static Navigation on the MeSH Concept Hierarchy
Figure 1 displays a snapshot of such an interface where shown next to each node label is the count of distinct
citations in the subtree rooted at that node. For this example, we assume that the user queries MEDLINE for the
nucleoprotein ―prothymosin‖ and his personal interests are reflected in the two indicated concepts, corresponding to two
independent lines of research related to prothymosin. A typical navigation starts with revealing the children of the root
ranked by their citation count, and is continued with expanding one or more of them, revealing their ranked children and so
on. Further, the user may click on a concept and inspect the attached citations. A similar interface and navigation method is
used by GoPubMed [5] and e-commerce sites, such as Amazon and eBay.
1
2. Efficient Navigation of Query Results Using Concept Hierarchies
The above static navigation method −same for every query result−is problematic when the MeSH hierarchy (or
one with similar properties) is used for categorization for the following reasons:
The massive size of the MeSH hierarchy (with 48,441 concept nodes) makes it challenging for the users to
effectively navigate to the desired concepts and browse the associated citations.
A substantial number of duplicate citations are introduced in the navigation tree of Figure 1, since each one of the
313 distinct citations is associated with several concepts. Specifically, the total count of citations in Figure 1 is
40,195.
II. BACKGROUND
Several systems have been developed to facilitate keyword search on PubMed using the MeSH concept hierarchy.
Pubmed itself allows the user to search for citations based on MeSH annotations. A keyword query ―histones [MeSH
Terms]‖ will retrieve all citations annotated with the MeSH term ―histones‖ in the MeSH hierarchy. The user can also limit
her search to a MeSH term by using additional filters, e.g., ―[majr]‖ to filter out all citations in the query result that don’t
have the term as their major term. These filters can be combined by using the Boolean connectives AND, OR, and NOT.
This interface poses significant challenges, even to experienced users, since the annotation process is manual and thus prone
to errors. The closest to BioNav is GoPubMed [7-11], which implements a static navigation method on the results of
PubMed. GoPubMed lists a predefined list of high-level MeSH concepts, such as ―Chemicals and Drugs,‖ ―Biological
Sciences,‖ and so on, and for each one of them displays the top-10 concepts. After a node expansion, its children are
revealed and ranked by the number of their attached citations, whereas BioNav reveals a selective and dynamic list of
descendant (not always children) nodes ranked by their estimated relevance to the user’s query. Further, BioNav uses a cost
model to decide which concepts to display at each step. BioNav belongs primarily to the categorization class, which is
especially suitable for this domain given the rich concept hierarchies available for biomedical data. We augment our
categorization techniques with simple ranking techniques. BioNav organizes the query results into a dynamic hierarchy, the
navigation tree. Each concept (node)of the hierarchy has a descriptive label.
The user then navigates this tree structure, in a top-down fashion, exploring the concepts of interest while ignoring
the rest Node that the user is not aware that the relevant results are available specifically on these nodes—she is only
interested in narrowing down the results, using a familiar concept hierarchy, instead of examining all the results The above
static—same for every query result—navigation method is problematic when the MeSH hierarchy (or one with similar
properties) is used for categorization for the following reasons.
III. PROPOSED SYSTEM ARCHITECTURE
Information overload is a common phenomenon encountered by users searching biomedical databases such as
PubMed. We encounter this problem; we resolve this problem by optimizing the query result time and minimize query result
set for easy user navigation.
Fig. 2: BioNav System Architecture
A. Architecture of BioIntelR System
The propose BIR system consists combination of ( shown in Fig 2 and 3 which shows the actual flow):
1. Web interfaces
2. Middle layer
3. Navigation system,
4. Programming utilizes
5. Data base
2
3. Efficient Navigation of Query Results Using Concept Hierarchies
Fig 3 system flow
Upon receiving a keyword query from the user, BioIntelR sends the query and Visualize the query results, BioNav
executes the same query against the MEDLINE database and retrieves only the IDs (PubMed Identifiers) of the citations in
the query result. The user interacts with system by using BioIntelR web browse to find the effective results of the search
criteria from PubMed. Previously the BioNav system, once the user issues a keyword query, PubMed—BioNav uses the
Entrez Programming Utilities—returns a list of citations, each associated with several MeSH concepts. BioNav constructs
an Initial Navigation Tree by attaching to each concept node of the MeSH concept hierarchy a list of its associated citations
BioNav reduces the size of the initial navigation tree by removing the nodes with empty results lists, while preserving the
ancestor/descendant relationships. The MeSH concept hierarchy is the starting point of the framework and is defined as
follows: Concept Hierarchy, Navigation Tree, Valid EdgeCut, Active Tree, Active Tree Visualization, and The navigation
model of BioNav which is used to device and evaluate algorithms .
Web Interface: Web interface is the user interface interacts with the BiointelR system, by specifying the search
criteria by specifying the search key words to visualize the optimized results from the system.
Middle Layer: The role of the middle is to provide an easy to use and understand interface for user to search
criteria against database to get the minimal result set for easy navigation and it reduces search result time.The middle laye r is
a file mainly consists of the schema of objects is created according underlying database, the file contains connection
parameter to connect the database, the middle layer Maps the search keywords to the database and validated path for the
search criteria .The layer acts as bridge between the user interface and the database. The schemas that we created must be
relevant to the end user business environment and vocabulary.
Navigation System:After the user issues a keyword query, BioNav initiates navigation by constructing the initial
active tree (which has a single component tree rooted at the MeSH root) and displaying its root to the user. Subsequently, the
user navigates the tree by performing one of the following actions on a given component subtree rooted at concept node n:
EXPAND, SHOWRESULTS, IGNORE, BACKTRACK this navigation process continues until the user finds all the
citations she is interested in.
Programming Utilities: Entrez Programming Utilities returns a list of citations, each associated with several
MeSH concepts
3
4. Efficient Navigation of Query Results Using Concept Hierarchies
Data Bases: MEDLINE database, fig .3 on which the PubMed search engine operates, contains over 18 million
citations and is currently growing at the rate of 500,000 new citations each year. The BioNav database is first populated wit h
the MeSH hierarchy, which is available online [12-15] and has more than 48,000 concept nodes. Then, the BioNav database
is populated with the associations of the MEDLINE citations to MeSH concepts.
B. Algorithm
Procedure. GenReducedTree
Input: Initial Navigation Tree I(n), the target concept c, and the desired number max N of nodes in the reduced tree
Output: A reduced tree with at most maxN nodes,including c
1. collect all nodes of I(n) in list L
2. create list L1 to store the nodes of the reduced tree
3. add to L1 a concept node in L with the same label as c and all its ancestors
4. while (sizeof(L)≤ maxN) repeat
5. select a node c0 uniformly at random from L
6. add c1 and all its ancestors to L1, excluding duplicates
7. create a tree I1(n) from the nodes in L1 preserving the parent-child relationship
8. return I1(n)
IV. IMPLEMENTATION
In this paper our proposed method consists following modules.
Query Search process module (or) Biomedical Search Systems module: PubMed– using a keyword search
interface. Currently, in an exploratory scenario where the user tries to find citations relevant to her line of research and hence
not known a priori, she submits an initially broad keyword- based query that typically returns a large number of results.
Subsequently, the user iteratively refines the query, if she has an idea of how to, by adding more keywords, and re-submits it,
until a relatively small number of results are returned. This refinement process is problematic because after a number of
iterations the user is not aware if she has over-specified the query, in which case relevant citations might be excluded from
the final query result. Query on PubMed is using the MeSH static concept hierarchy , thus utilizing the initiative of the US
National Library of Medicine (NLM) to build and maintain such a comprehensive structure. Each citation in MEDLINE is
associated with several MeSH concepts in two ways: (i) by being explicitly annotated with them, and (ii) by mentioning
those in their text . Since these associations are provided by PubMed, a relatively straightforward interface to navigate the
query result would first attach the citations to the corresponding MeSH concept nodes and then let the user navigate the
navigation tree
Dynamic navigation tree module: navigation tree. Figdisplays a snapshot of such an interface where shown next
to each node label is the count of distinct citations in the subtree rooted at that node. A typical navigation starts by reve aling
the children of the root ranked by their citation count, and is continued by the user expanding on or more of them, revealing
their ranked children and so on, until she clicks on a concept and inspects the citations attached to it. A similar interface and
navigation method is used by e-commerce sites, such as Amazon and eBay. For this example, we assume that the user will
navigate to the three indicated concepts corresponding to three independent lines of research related to prothymosin
BioNav introduces a dynamic navigation method that depends on the particular query result at hand and is demonstrated in
Fig The query results are attached to the corresponding MeSH concept nodes as in Fig. but then the navigation proceeds
differently. The key action on the interface is the expansion of a node that selectively reveals a ranked list of descendant (not
necessarily children) concepts, instead of simply showing all its children.
Hierarchy navigation web (interface) search module: BioNav belongs primarily to the categorization class, which
is ideal for this domain given the rich concept hierarchies (e.g., MeSH ) available for biomedical data. We augment our
categorization techniques with simple ranking techniques. BioNav organizes the query results into a dynamic hierarchy, the
navigation tree. Each concept (node) of the hierarchy has a descriptive label. The user then navigates this tree structure, in a
top-down fashion, exploring the concepts of interest while ignoring the rest.
Query Workload online operation module: On-Line Operation. Upon receiving a keyword query from the user,
BioNav executes the same query against the MEDLINE database and retrieves only the IDs
(Pub Med Identifiers) of the citations in the query result. This is done using the ESearch utility of the Entrez Programming
Utilities (eUtils) . eUtils are a collection of web interfaces to PubMed for issuing a query and downloading the results with
various levels of detail and in a variety of formats. Next, the navigation tree is constructed by retrieving the MeSH concept s
associated with each citation in the query result from the BioNav database. This is possible since MeSH concepts have tree
identifiers encoding their location in the MeSH hierarchy, which are also retrieved from the BioNav database. This process is
done once for each user query.
V. RESULT ANALYSIS
Experimental Evaluation We evaluated the difference between the BioIntelR and BioNav systems in terms of both
average Navigation cost and expansion time performance Other traditional measures of quality, such as precision and recall,
are not applicable to our scenario as the objective is to minimize the tree navigation cost and not to classify we show that the
BioIntelR method, which is evaluated using middle layer and adopted BioNav system and the BioNav system Heuristic-
4
5. Efficient Navigation of Query Results Using Concept Hierarchies
ReducedOpt algorithm, leads to considerably smaller navigation cost for a set of real queries on the MEDLINE database and
navigations on the MeSH hierarchy. we compare the optimal algorithm (Opt-EdgeCut) with Heuristic-ReducedOpt and
show that the heuristic is a good approximation of the optimal. These experiments were executed on a reduced navigation
tree (20 nodes), constructed from the original query navigation tree for each query, since Opt-EdgeCut is prohibitively
expensive for most navigation trees. Finally, shows that the execution time of Heuristic-ReducedOpt is small enough to
facilitate interactivetime use navigation. The experiments were executed on a Windows XP Professional machine with 3
GHz CPU and 2 GB of main memory, running Windows XP Professional. All algorithms were implemented in Java and
Oracle 10g was used as the database. These comparisons shown in Fig 4 and 5.
Fig. 4. Overall navigation cost comparison for biochemistry and medicine
Fig. 5. Overall navigation cost comparison
VI. CONCLUSIONS
In this paper, we presented the BioNav system which organize the query results according to user associations to
concepts of the MeSH concept hierarchy, and provide a dynamic navigation method that minimizes the information overload
observed by the user. When the user expands a MeSH concept on our web interface, BioNav reveals only a selective list of
descendant concepts, instead of simply showing all its children, ranked based on their estimated relevance to the user's
query. Our complexity result proved that the problem of expanding the navigation tree in a way that minimizes the user's
navigation cost.
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