Probabilistic latent semantic analysis: Difference between revisions

Revision as of 15:44, 7 February 2017

Revision as of 16:27, 1 May 2017

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PLSA has applications in [[information retrieval]] and [[information filtering|filtering]], [[natural language processing]], [[machine learning]] from text, and related areas.

It is reported that the [[aspect model]] used in the probabilistic latent semantic analysis has severe [[overfitting]] problems.<ref>{{cite journal|title=Latent Dirichlet Allocation|journal=Journal of Machine Learning Research|year=2003|first=David M.|last=Blei|author2=Andrew Y. Ng |author3=Michael I. Jordan |volume=3|pages=993–1022|id= |url=http://jmlr.csail.mit.edu/papers/volume3volumep3/blei03a/blei03a.pdf|doi=10.1162/jmlr.2003.3.4-5.993}}</ref>

In 2012, pLSA has also been used in the [[bioinformatics]] context, for prediction of [[gene ontology]] biomolecular annotations.<ref>[http://home.dei.polimi.it/chicco/Wcci2012_DavideChicco_et_al.pdfPinoli et al, ''"Probabilistic Latent Semantic Analysis for prediction of Gene Ontology annotations"'', MarcoProceedings Masseroli, Davide Chicco, Pietro Pinoli.of IEEE WCCI 2012 - the 2012 IEEE World Congress on Computational Intelligence proceedings. Brisbane, Australia, June 2012. ([https://doi.org/10.1109/IJCNN.2012.pdf)6252767]</ref>

==Extensions ==