Probabilistic latent semantic analysis: Difference between revisions

Revision as of 18:26, 14 April 2014

Revision as of 22:14, 23 July 2014

Line 21:

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|coauthorsauthor2=Andrew Y. Ng, |author3=Michael I. Jordan |volume=3|pages=993–1022|id= |url=http://jmlr.csail.mit.edu/papers/volume3/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.pdf ''"Probabilistic Latent Semantic Analysis for prediction of Gene Ontology annotations"'', Marco Masseroli, Davide Chicco, Pietro Pinoli. IEEE WCCI 2012 - the 2012 IEEE World Congress on Computational Intelligence proceedings. Brisbane, Australia, June 2012. (.pdf)]</ref>