Latent Dirichlet Allocation
Blei et al., 2003, Latent Dirichlet Allocation (Journal of Machine Learning Research)
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4.4 A geometric interpretation
- Compare unigram, mixture-of-unigrams, pLSI and LDA geometrically.All work on the word simplex (distributions over words); \(k\) topics span a topic simplex inside it. Unigram: one point for all words. Mixture of unigrams: each document at one corner of the topic simplex. pLSI: an empirical distribution with one point per training document. LDA: a smooth distribution over the topic simplex, sampled once per document.
Mixture of unigrams: corners only; pLSI: × at training documents; LDA: smooth density (contours) - Blei et al., 2003, Latent Dirichlet Allocation (Journal of Machine Learning Research), §4.4, pp. 1001–1002
Source
- David M. Blei, Andrew Y. Ng and Michael I. Jordan. 2003. Latent Dirichlet Allocation. In Journal of Machine Learning Research, pp. 993–1022. https://www.jmlr.org/papers/v3/blei03a.html