Probabilistic Latent Semantic Indexing

  title={Probabilistic Latent Semantic Indexing},
  author={Thomas Hofmann},
Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fitted from a training corpus of text documents by a generalization of the Expectation Maximization algorithm, the utilized model is able to deal with domain{speci c synonymy as well as with polysemous words. In contrast to standard Latent Semantic Indexing (LSI) by Singular Value Decomposition, the probabilistic variant… CONTINUE READING
Highly Influential
This paper has highly influenced 12 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 120 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 83 extracted citations

120 Citations

Citations per Year
Semantic Scholar estimates that this publication has 120 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.

Similar Papers

Loading similar papers…