Matrix Factorization and Latent Semantic Indexing Problems with Lexical semantics Ambiguity and association in natural language Polysemy: Words often have a multitude of meanings and different types of usage( more severe in very heterogeneous collections The vector space model is unable to discriminate between different meanings of the same word, sme(d,g)<cos(∠(,q)Matrix Factorization and Latent Semantic Indexing 27 Problems with Lexical Semantics ▪ Ambiguity and association in natural language ▪ Polysemy: Words often have a multitude of meanings and different types of usage (more severe in very heterogeneous collections). ▪ The vector space model is unable to discriminate between different meanings of the same word. LSI