Topic tracking using chronological term ranking

Date
2013-10
Advisor
Instructor
Source Title
27th International Symposium on Computer and Information Sciences
Print ISSN
Electronic ISSN
Publisher
Volume
Issue
Pages
353 - 361
Language
English
Type
Conference Paper
Journal Title
Journal ISSN
Volume Title
Abstract

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.

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Keywords
News articles, Real applications, Similarity measure, Standard tests, Topic detection and tracking, Topic tracking, Information analysis, Information retrieval systems
Citation
Published Version (Please cite this version)