Term Context Models for Information Retrieval


At their heart, most if not all information retrieval models
utilize some form of term frequency. The notion is that the
more often a query term occurs in a document, the more likely it is that document meets an information need. We examine an alternative. We propose a model which assesses the presence of a term in a document not by looking at the actual occurrence of that term, but by a set of nonindependent supporting terms, i.e. context. This yields a weighting for terms in documents which is different from and complementary to tf-based methods, and is beneficial for retrieval.