Building concept network-based user profile for personalized web search
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Han-Joon | - |
dc.contributor.author | Lee, Sungjick | - |
dc.contributor.author | Lee, Byungjeong | - |
dc.contributor.author | Kang, Sooyong | - |
dc.date.accessioned | 2022-12-20T11:45:27Z | - |
dc.date.available | 2022-12-20T11:45:27Z | - |
dc.date.created | 2022-09-16 | - |
dc.date.issued | 2010-09 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/173712 | - |
dc.description.abstract | This paper presents a novel way of building the user profile of concept network for personalized search. The user profile is defined as a concept network, in which each concept is approximately represented with the formal concept analysis (FCA) theory. We assume that a concept, called 'session interest concept', subsume a user's query intention during a query session and it can reflect the user's preference. Whenever a user issues his/her query, a session interest concept is generated. Then, new concepts are merged into the current concept network (i.e., a user profile) in which recent user preferences are accumulated. According to FCA, a session interest concept is defined as a pair of extent and intent where the extent covers a set of documents selected by the user among the search results and the intent covers a set of keyword features extracted from the selected documents. And, in order to make a concept network grow, we need to calculate the similarity between a new concept and existing concepts, and to this end, we use a reference concept hierarchy called Open Directory Project. The user profile of concept network is eventually used to expand a user's initial query. The empirical results show that our approach improves the accuracy of search results in terms of personal preference. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | IEEE | - |
dc.title | Building concept network-based user profile for personalized web search | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kang, Sooyong | - |
dc.identifier.doi | 10.1109/ICIS.2010.56 | - |
dc.identifier.scopusid | 2-s2.0-78649306766 | - |
dc.identifier.bibliographicCitation | Proceedings - 9th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2010, pp.567 - 572 | - |
dc.relation.isPartOf | Proceedings - 9th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2010 | - |
dc.citation.title | Proceedings - 9th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2010 | - |
dc.citation.startPage | 567 | - |
dc.citation.endPage | 572 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | Concept networks | - |
dc.subject.keywordPlus | Keyword extraction | - |
dc.subject.keywordPlus | Personalized search | - |
dc.subject.keywordPlus | Query expansion | - |
dc.subject.keywordPlus | User profile | - |
dc.subject.keywordPlus | Information retrieval | - |
dc.subject.keywordPlus | Information science | - |
dc.subject.keywordPlus | Websites | - |
dc.subject.keywordAuthor | Concept network | - |
dc.subject.keywordAuthor | Information retrieval | - |
dc.subject.keywordAuthor | Keyword extraction | - |
dc.subject.keywordAuthor | Personalized search | - |
dc.subject.keywordAuthor | Query expansion | - |
dc.subject.keywordAuthor | User profile | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/5591001 | - |
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