Search engines are the most commonly used type of tool for finding relevant information on the Internet. However, today's search engines are far from perfect. Typical search queries are short, often one or two words, and can be ambiguous therefore returning inappropriate results. Contextual information retrieval (CIR) is a critical technique for these search engines to facilitate queries and return relevant information. Despite its importance, little progress has been made in CIR due to the difficulty of capturing and representing contextual information about users. Numerous contextual information retrieval approaches exist today, but to the best of our knowledge none of them offer a similar service to the one proposed in this paper. This paper proposes an alternative framework for contextual information retrieval from the WWW. The framework aims to improve query results (or make search results more relevant) by constructing a contextual profile based on a user's behaviour, their preferences, and a shared knowledge base, and using this information in the search engine framework to find and return relevant information.
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