Probabilistic latent semantic analysis: Difference between revisions

Revision as of 19:32, 23 March 2023

Revision as of 19:33, 23 March 2023

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PLSA may be used in a discriminative setting, via [[Fisher kernel]]s.<ref>Thomas Hofmann, [https://papers.nips.cc/paper/1654-learning-the-similarity-of-documents-an-information-geometric-approach-to-document-retrieval-and-categorization.pdf ''Learning the Similarity of Documents : an information-geometric approach to document retrieval and categorization''], [[Advances in Neural Information Processing Systems]] 12, pp-914-920, [[MIT Press]], 2000</ref>

PLSA has applications in [[information retrieval]] and [[information filtering|filtering]](citation needed), [[natural language processing]], [[machine learning]] from text, [[bioinformatics]],<ref>{{Cite conference|chapter=Enhanced probabilistic latent semantic analysis with weighting schemes to predict genomic annotations|conference=The 13th IEEE International Conference on BioInformatics and BioEngineering|last1=Pinoli|first1=Pietro|last2=et|first2=al.|title= Proceedings of IEEE BIBE 2013 |date=2013|publisher=IEEE|pages=1–4|language=en|doi=10.1109/BIBE.2013.6701702|isbn=978-147993163-7}}

</ref> and related areas.