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Conference Paper: An Efficient Algorithm for Incremental Update of Concept Spaces

TitleAn Efficient Algorithm for Incremental Update of Concept Spaces
Authors
Keywordsconcept space
thesaurus
information retrieval
text mining
Issue Date2001
PublisherSpringer.
Citation
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-02), 2001. In Chen, MS., Yu, PS and Liu, B. (Eds). Advances in Knowledge Discovery and Data Mining, p. 368-380. Berlin, Heidelberg: Springer, 2001 How to Cite?
AbstractThe vocabulary problem in information retrieval arises because authors and indexers often use different terms for the same concept. A thesaurus defines mappings between different but related terms. It is widely used in modern information retrieval systems to solve the vocabulary problem. Chen et al. proposed the concept space approach to automatic thesaurus construction. A concept space contains the associations between every pair of terms. Previous research studies show that concept space is a useful tool for helping information searchers in revising their queries in order to get better results from information retrieval systems. The construction of a concept space, however, is very computationally intensive. In this paper, we propose and evaluate an efficient algorithm for the incremental update of concept spaces. In our model, only strong associations are maintained, since they are most useful in thesauri construction. Our algorithm uses a pruning technique to avoid computing weak associations to achieve efficiency.
Persistent Identifierhttp://hdl.handle.net/10722/93432
ISBN

 

DC FieldValueLanguage
dc.contributor.authorCheung, KMen_HK
dc.contributor.authorKao, CMen_HK
dc.contributor.authorCheung, DWLen_HK
dc.contributor.authorNg, CYen_HK
dc.date.accessioned2010-09-25T15:00:59Z-
dc.date.available2010-09-25T15:00:59Z-
dc.date.issued2001en_HK
dc.identifier.citationPacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-02), 2001. In Chen, MS., Yu, PS and Liu, B. (Eds). Advances in Knowledge Discovery and Data Mining, p. 368-380. Berlin, Heidelberg: Springer, 2001-
dc.identifier.isbn978-3-540-43704-8-
dc.identifier.urihttp://hdl.handle.net/10722/93432-
dc.description.abstractThe vocabulary problem in information retrieval arises because authors and indexers often use different terms for the same concept. A thesaurus defines mappings between different but related terms. It is widely used in modern information retrieval systems to solve the vocabulary problem. Chen et al. proposed the concept space approach to automatic thesaurus construction. A concept space contains the associations between every pair of terms. Previous research studies show that concept space is a useful tool for helping information searchers in revising their queries in order to get better results from information retrieval systems. The construction of a concept space, however, is very computationally intensive. In this paper, we propose and evaluate an efficient algorithm for the incremental update of concept spaces. In our model, only strong associations are maintained, since they are most useful in thesauri construction. Our algorithm uses a pruning technique to avoid computing weak associations to achieve efficiency.-
dc.languageengen_HK
dc.publisherSpringer.en_HK
dc.relation.ispartofAdvances in Knowledge Discovery and Data Miningen_HK
dc.subjectconcept space-
dc.subjectthesaurus-
dc.subjectinformation retrieval-
dc.subjecttext mining-
dc.titleAn Efficient Algorithm for Incremental Update of Concept Spacesen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailCheung, KM: fcheung@eti.hku.hken_HK
dc.identifier.emailKao, CM: kao@cs.hku.hken_HK
dc.identifier.emailCheung, DWL: dcheung@cs.hku.hken_HK
dc.identifier.emailNg, CY: cytrix@gmail.comen_HK
dc.identifier.authorityKao, CM=rp00123en_HK
dc.identifier.authorityCheung, DWL=rp00101en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/3-540-47887-6_37-
dc.identifier.hkuros71020en_HK

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