This paper presents a novel context matching technique for the retrieval of web documents. The aim of the technique is to dynamically generate a context-based 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 to occur multiple times within 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 large document. The proposed technique has been implemented and the experiments were conducted using a TREC benchmark database. A comparative analysis shows that context matching significantly improves retrieval effectiveness and outperforms previously published results.