  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.
