Topic tracking using chronological term ranking

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dc.citation.epage361en_US
dc.citation.spage353en_US
dc.contributor.authorAcun, Bilgeen_US
dc.contributor.authorBaşpınar, Alperen_US
dc.contributor.authorOǧuz, Ekinen_US
dc.contributor.authorSaraç, M.İlkeren_US
dc.contributor.authorCan, Fazlıen_US
dc.coverage.spatialParis, Franceen_US
dc.date.accessioned2016-02-08T12:05:58Z
dc.date.available2016-02-08T12:05:58Z
dc.date.issued2013-10en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionDate of Conference: 3-4 October 2012
dc.descriptionConference name: 27th International Symposium on Computer and Information Sciences (ISCIS 2012)
dc.description.abstractTopic tracking (TT) is an important component of topic detection and tracking (TDT) applications. TT algorithms aim to determine all subsequent stories of a certain topic based on a small number of initial sample stories. We propose an alternative similarity measure based on chronological term ranking (CTR) concept to quantify the relatedness among news articles for topic tracking. The CTR approach is based on the fact that in general important issues are presented at the beginning of news articles. By following this observation we modify the traditional Okapi BM25 similarity measure using the CTR concept. Using a large standard test collection we show that our method provides a statistically significantly improvement with respect to the Okapi BM25 measure. The highly successful performance indicates that the approach can be used in real applications. © 2013 Springer-Verlag London.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T12:05:58Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2013en
dc.identifier.doi10.1007/978-1-4471-4594-3_36en_US
dc.identifier.urihttp://hdl.handle.net/11693/27942
dc.language.isoEnglishen_US
dc.relation.isversionofhttps://doi.org/10.1007/978-1-4471-4594-3_36en_US
dc.source.title27th International Symposium on Computer and Information Sciencesen_US
dc.subjectNews articlesen_US
dc.subjectReal applicationsen_US
dc.subjectSimilarity measureen_US
dc.subjectStandard testsen_US
dc.subjectTopic detection and trackingen_US
dc.subjectTopic trackingen_US
dc.subjectInformation analysisen_US
dc.subjectInformation retrieval systemsen_US
dc.titleTopic tracking using chronological term rankingen_US
dc.typeConference Paperen_US

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