biterm主题模型

The latest code has been moved into Gibhub, and this site will no longer be updated. BTM: https://github.com/xiaohuiyan/BTM online BTM: https://github.com/xiaohuiyan/OnlineBTM bursty BTM: https://github.com/xiaohuiyan/BurstyBTM The papers can be found on my homepage: http://www.shortext.org Biterm Topic Model (BTM) is a topic model developed for short text (need to set a window length when generating biterms for nomral text), like microblogs and webpage titles. It learns topics by modeling the generation process of word co-occurrences (referred as biterms), rather than word-document co-occurrences. ### 1. Model Description ### In BTM, the distribution of a biterm b=(w1,w2) is > P(w1,w2) = sum\_k{P(w1|

btm-v0.3
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