Acun, BilgeBaşpınar, AlperOǧuz, EkinSaraç, M.İlkerCan, Fazlı2016-02-082016-02-082013-10http://hdl.handle.net/11693/27942Date of Conference: 3-4 October 2012Conference name: 27th International Symposium on Computer and Information Sciences (ISCIS 2012)Topic 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.EnglishNews articlesReal applicationsSimilarity measureStandard testsTopic detection and trackingTopic trackingInformation analysisInformation retrieval systemsConference Paper10.1007/978-1-4471-4594-3_36