Basit öğe kaydını göster

dc.contributor.authorKocabas, Ilker
dc.contributor.authorDincer, Bekir Taner
dc.contributor.authorKaraoglan, Bahar
dc.date.accessioned2020-11-20T16:18:09Z
dc.date.available2020-11-20T16:18:09Z
dc.date.issued2014
dc.identifier.issn1386-4564
dc.identifier.issn1573-7659
dc.identifier.urihttps://doi.org/10.1007/s10791-013-9225-4
dc.identifier.urihttps://hdl.handle.net/20.500.12809/3490
dc.descriptionDincer, Bekir Taner/0000-0002-0660-7239en_US
dc.descriptionWOS: 000332963700003en_US
dc.description.abstractIn this article, we introduce an out-of-the-box automatic term weighting method for information retrieval. The method is based on measuring the degree of divergence from independence of terms from documents in terms of their frequency of occurrence. Divergence from independence has a well-establish underling statistical theory. It provides a plain, mathematically tractable, and nonparametric way of term weighting, and even more it requires no term frequency normalization. Besides its sound theoretical background, the results of the experiments performed on TREC test collections show that its performance is comparable to that of the state-of-the-art term weighting methods in general. It is a simple but powerful baseline alternative to the state-of-the-art methods with its theoretical and practical aspects.en_US
dc.description.sponsorshipTUBITAK, The Scientific and Technological Research Council of TurkeyTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [107E192]en_US
dc.description.sponsorshipAuthors are thankful to anonymous reviewers for their valuable comments and advices that make this a better paper, and also to Craig Macdonald, Giambattista Amati, and Iadh Ounis for their kind helps. Index term weighting by DFI is developed under the project titled "Design of A Statistical Information Retrieval System'', and supported by TUBITAK, The Scientific and Technological Research Council of Turkey, with Project No: 107E192. Any opinions, findings and conclusions or recommendations expressed in this material are the authors' and do not necessarily reflect those of the sponsor.en_US
dc.item-language.isoengen_US
dc.publisherSpringeren_US
dc.item-rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectInformation Retrievalen_US
dc.subjectNonparametric Index Term Weightingen_US
dc.subjectStatistical Dependenceen_US
dc.subjectPearson's Chi-Square Statisticsen_US
dc.titleA nonparametric term weighting method for information retrieval based on measuring the divergence from independenceen_US
dc.item-typearticleen_US
dc.contributor.departmenten_US
dc.contributor.departmentTemp[Kocabas, Ilker; Karaoglan, Bahar] Ege Univ, Int Comp Inst, Izmir, Turkey -- [Dincer, Bekir Taner] Mugla Univ, Dept Stat, Mugla, Turkey -- [Dincer, Bekir Taner] Mugla Univ, Dept Comp Engn, Mugla, Turkeyen_US
dc.identifier.doi10.1007/s10791-013-9225-4
dc.identifier.volume17en_US
dc.identifier.issue2en_US
dc.identifier.startpage153en_US
dc.identifier.endpage176en_US
dc.relation.journalInformation Retrievalen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


Bu öğenin dosyaları:

DosyalarBoyutBiçimGöster

Bu öğe ile ilişkili dosya yok.

Bu öğe aşağıdaki koleksiyon(lar)da görünmektedir.

Basit öğe kaydını göster