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 non-independent 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.
conditional random fields maximum entropy context-based retrieval