Trend detection model

Authors:
Noriaki Kawamae;Ryuichiro Higashinaka
Affiliations:
NTT Communication Science Laboratories, Chiba, Japan;NTT Communication Science Laboratories, yokosuka, Japan
Venue:
Proceedings of the 19th international conference on World wide web
Year:
2010

Citing 2
Cited 3

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Abstract

This paper presents a topic model that detects topic distributions over time. Our proposed model, Trend Detection Model (TDM) introduces a latent trend class variable into each document. The trend class has a probability distribution over topics and a continuous distribution over time. Experiments using our data set show that TDM is useful as a generative model in the analysis of the evolution of trends.