Probabilistic latent semantic analysis: Difference between revisions

Revision as of 12:11, 29 May 2018

Revision as of 17:04, 11 May 2020

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** Asymmetric: MASHA ("Multinomial ASymmetric Hierarchical Analysis")<ref>Alexei Vinokourov and Mark Girolami, [http://citeseer.ist.psu.edu/rd/30973750,455249,1,0.25,Download/http://citeseer.ist.psu.edu/cache/papers/cs/22961/http:zSzzSzcis.paisley.ac.ukzSzvino-ci0zSzvinokourov_masha.pdf/vinokourov02probabilistic.pdf A Probabilistic Framework for the Hierarchic Organisation and Classification of Document Collections], in ''Information Processing and Management'', 2002</ref>

** Symmetric: HPLSA ("Hierarchical Probabilistic Latent Semantic Analysis")<ref>Eric Gaussier, Cyril Goutte, Kris Popat and Francine Chen,

[http://www.xrce.xerox.com/Research-Development/Publications/2002-004 A Hierarchical Model for Clustering and Categorising Documents] {{Webarchive|url=https://web.archive.org/web/20160304033131/http://www.xrce.xerox.com/Research-Development/Publications/2002-004 |date=2016-03-04 }}, in "Advances in Information Retrieval -- Proceedings of the 24th [[Information Retrieval Specialist Group|BCS-IRSG]] European Colloquium on IR Research (ECIR-02)", 2002</ref>

* Generative models: The following models have been developed to address an often-criticized shortcoming of PLSA, namely that it is not a proper generative model for new documents.

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==External links==

*[https://web.archive.org/web/20050120213347/http://www.cs.brown.edu/people/th/papers/Hofmann-UAI99.pdf Probabilistic Latent Semantic Analysis]

*[https://web.archive.org/web/20171113005121/http://www.semanticquery.com/archive/semanticsearchart/researchpLSA.html Complete PLSA DEMO in C#]

{{DEFAULTSORT:Probabilistic Latent Semantic Analysis}}