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Theme Topic Mixture Model: A Graphical Model for Document Representation
Type of publication: Conference paper
Citation: keller:pascal-wshp:2004
Booktitle: Pascal Workshop on Text Mining and Understanding
Year: 2004
Note: IDIAP-RR 04-05
Crossref: keller:rr04-05:
Abstract: Documents are usually represented in the bag-of-word space. However, this representation does not take into account the possible relations between words. We propose here a graphical model for representing documents: the Theme Topic Mixture Model (TTMM). This model assumes two types of relations among textual data. Topics link words to each other and Themes gather documents with particular distribution over the topics. This paper defines the TTMM, compares it to the related Latent Dirichlet Allocation (LDA) model (Blei, 2003) and reports some interesting empirical results.
Userfields: ipdmembership={learning},
Projects Idiap
Authors Keller, Mikaela
Bengio, Samy
Added by: [UNK]
Total mark: 0
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