Volume 5 Number 5 (May 2010)
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JSW 2010 Vol.5(5): 482-489 ISSN: 1796-217X
doi: 10.4304/jsw.5.5.482-489

Topic Tracking with Dynamic Topic Model and Topic-based Weighting Method

Xiaoyan Zhang, Ting Wang
Department of Computer Science and Technology, School of Computer, National University of Defense Technology No.137, Yanwachi Street, Changsha, Hunan 410073, P.R.China

Abstract—In topic tracking, a topic is usually described by several stories. How to represent a topic is always an issue and a difficult problem in the research on topic tracking. To emphasis the topic in stories, we provide an improved topicbased tf*idf weighting method to measure the topical importance of the features in the representation model. To overcome the topic drift problem and filter the noise existed in the tracked topic description, a dynamic topic model is proposed based on the static model. It extends the initial topic model with the information from the incoming related stories and filters the noise using the latest unrelated story. The topic tracking systems are implemented on the TDT4 Chinese corpus. The experimental results indicate that both the new weighting method and the dynamic model can improve the tracking performance.

Index Terms—topic tracking, topic drift, dynamic topic model, feature weighting.


Cite: Xiaoyan Zhang, Ting Wang, "Topic Tracking with Dynamic Topic Model and Topic-based Weighting Method," Journal of Software vol. 5, no. 5, pp. 482-489, 2010.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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