Probabilistic Latent Semantic Indexing

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 todeal 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 has a solid statistical foundation and de nes a proper generative data model. Retrieval experiments on a number of test collections indicate substantial performance gains over direct term matching methods as well as over LSI. In particular, the combination of models with di erent dimensionalities has proven to be advantageous.

• Type: Conference
• Year: 1999
• Where: SIGIR
• Authors: Thomas Hofmann
• Keywords: Information Management, Latent Class Model, Latent Semantic Indexing, Semantic Indexing LSI, SIGIR 1999