A Novel context-based technique for web information retrieval

In this paper we present context matching, a novel context-based technique for the ad-hoc retrieval of web documents. The aim of the technique is to dynamically generate a measure of document term significance during retrieval that can be used as a substitute or co-contributor of the term frequency measure. Unlike term frequency, which relies on a term occurring multiple times in a document to be considered significant, context matching is based on the notion that if a term in a given document occurs in that document in the context of the query, then that term is deemed to be significant. Context matching has the ability to potentially determine a term to be significant even if it occurs only once in a document. Vice versa, it also has the ability to determine a term to be insignificant, even if occurs frequently within a document. We show how expanded terms generated by a typical query expansion technique can be used effectively as query context for context matching. The technique is ideally suited to the nature of web information retrieval and we show how context matching significantly improves retrieval accuracy through experimental results on TREC web benchmark data.