NDLI: An on-line adaptive topic evolution model in web discussions

Content Provider	IEEE Xplore Digital Library
Author	Chunming Yang Hui Zhang Dawen Shi
Copyright Year	2013
Description	Author affiliation: Sch. of Comput. Sci. & Technol., Southwest Univ. of Sci. & Technol., Mianyang, China (Chunming Yang; Hui Zhang; Dawen Shi)
Abstract	Topic evolution is an important research task for Topic Detection and Tracking (TDT), studying how the topics evolve over time on textual data. On the Web forum, topics are often interactive, which means that new topics emerge and old ones decay and the number of topics is always in a dynamic change. This paper presents an on-line adaptive topic evolution model based on Latent Dirichlet Allocation (LDA). This model uses the posterior of topics and word distribution in historical time window to adjust the prior of current by linear weighted, which is able to find the new topics and the vanished ones in text streams and automatically update the topic number. The experiment shows that the proposed model can identify the topic changes in terms of number well, and analyze their evolution in time and content; hence the hot spots can be discovered in time.
Sponsorship	IEEE Circuits Syst. Soc.
Starting Page	847
Ending Page	852
File Size	320614
Page Count	6
File Format	PDF
ISBN	9781467352536
DOI	10.1109/FSKD.2013.6816312
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Topic Evolution Latent Dirichlet Allocation Adaptation models Analytical models Market research Educational institutions Vectors Data models Topic Model Resource management
Content Type	Text
Resource Type	Article

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