Personalized Web Search by Constructing Semantic Clusters of User Profiles
Identifieur interne : 000279 ( Istex/Corpus ); précédent : 000278; suivant : 000280Personalized Web Search by Constructing Semantic Clusters of User Profiles
Auteurs : John Garofalakis ; Theodoula Giannakoudi ; Agoritsa VopiSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2008.
Abstract
Abstract: During the recent years the Web has been developed rapidly making the efficient searching of information difficult and time-consuming. In this work, we propose a web search personalization methodology by coupling data mining techniques with the underlying semantics of the web content. To this purpose, we exploit reference ontologies that emerge from web catalogs (such as ODP), which can scale to the growth of the web. Our methodology uses ontologies to provide the semantic profiling of users’ interests based on the implicit logging of their behavior and the on-the-fly semantic analysis and annotation of the web results summaries.
Url:
DOI: 10.1007/978-3-540-85565-1_30
Links to Exploration step
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<ChapterHeader><AuthorGroup><Author AffiliationIDS="Aff1 Aff2"><AuthorName DisplayOrder="Western"><GivenName>John</GivenName>
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<Author AffiliationIDS="Aff1 Aff2"><AuthorName DisplayOrder="Western"><GivenName>Theodoula</GivenName>
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<Author AffiliationIDS="Aff1 Aff2"><AuthorName DisplayOrder="Western"><GivenName>Agoritsa</GivenName>
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<Affiliation ID="Aff1"><OrgDivision>RA Computer Technology Institute Telematics Center Department</OrgDivision>
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<Affiliation ID="Aff2"><OrgDivision>Computer Engineering & Informatics Dept</OrgDivision>
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<Country>Greece</Country>
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<Para>During the recent years the Web has been developed rapidly making the efficient searching of information difficult and time-consuming. In this work, we propose a web search personalization methodology by coupling data mining techniques with the underlying semantics of the web content. To this purpose, we exploit reference ontologies that emerge from web catalogs (such as ODP), which can scale to the growth of the web. Our methodology uses ontologies to provide the semantic profiling of users’ interests based on the implicit logging of their behavior and the on-the-fly semantic analysis and annotation of the web results summaries.</Para>
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<Keyword>Web Usage Mining</Keyword>
<Keyword>Semantic Annotation</Keyword>
<Keyword>Clustering</Keyword>
<Keyword>Ontology</Keyword>
<Keyword>User Profiles</Keyword>
<Keyword>Web Search</Keyword>
<Keyword>Personalization</Keyword>
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<abstract lang="en">Abstract: During the recent years the Web has been developed rapidly making the efficient searching of information difficult and time-consuming. In this work, we propose a web search personalization methodology by coupling data mining techniques with the underlying semantics of the web content. To this purpose, we exploit reference ontologies that emerge from web catalogs (such as ODP), which can scale to the growth of the web. Our methodology uses ontologies to provide the semantic profiling of users’ interests based on the implicit logging of their behavior and the on-the-fly semantic analysis and annotation of the web results summaries.</abstract>
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