A novel term weighting scheme based on discrimination power obtained from past retrieval results

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dc.contributor.authorSong, Sa-Kwangko
dc.contributor.authorMyaeng, Sung-Hyonko
dc.date.accessioned2013-03-12T12:27:02Z-
dc.date.available2013-03-12T12:27:02Z-
dc.date.created2012-10-11-
dc.date.created2012-10-11-
dc.date.issued2012-09-
dc.identifier.citationINFORMATION PROCESSING & MANAGEMENT, v.48, no.5, pp.919 - 930-
dc.identifier.issn0306-4573-
dc.identifier.urihttp://hdl.handle.net/10203/102324-
dc.description.abstractTerm weighting for document ranking and retrieval has been an important research topic in information retrieval for decades. We propose a novel term weighting method based on a hypothesis that a term's role in accumulated retrieval sessions in the past affects its general importance regardless. It utilizes availability of past retrieval results consisting of the queries that contain a particular term, retrieved documents, and their relevance judgments. A term's evidential weight, as we propose in this paper, depends on the degree to which the mean frequency values for the relevant and non-relevant document distributions in the past are different. More precisely, it takes into account the rankings and similarity values of the relevant and non-relevant documents. Our experimental result using standard test collections shows that the proposed term weighting scheme improves conventional TF*IDF and language model based schemes. It indicates that evidential term weights bring in a new aspect of term importance and complement the collection statistics based on TF*IDF. We also show how the proposed term weighting scheme based on the notion of evidential weights are related to the well-known weighting schemes based on language modeling and probabilistic models. (C) 2012 Elsevier Ltd. All rights reserved.-
dc.languageEnglish-
dc.publisherELSEVIER SCI LTD-
dc.subjectINFORMATION-
dc.titleA novel term weighting scheme based on discrimination power obtained from past retrieval results-
dc.typeArticle-
dc.identifier.wosid000307682100009-
dc.identifier.scopusid2-s2.0-84864284059-
dc.type.rimsART-
dc.citation.volume48-
dc.citation.issue5-
dc.citation.beginningpage919-
dc.citation.endingpage930-
dc.citation.publicationnameINFORMATION PROCESSING & MANAGEMENT-
dc.identifier.doi10.1016/j.ipm.2012.03.004-
dc.contributor.localauthorMyaeng, Sung-Hyon-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorTerm weighting-
dc.subject.keywordAuthorEvidential weight-
dc.subject.keywordAuthorDiscrimination power-
dc.subject.keywordAuthorLanguage model-
dc.subject.keywordAuthorProbabilistic model-
dc.subject.keywordPlusINFORMATION-
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