: The Web is huge, unstructured and diverse in quality, which makes searching for information difficult. In practice, few of the documents returned by a search engine are valuable to a user. Which documents are valuable depends on the context of the query. Some adequate context information provided in addition to keywords can improve significantly search precision. In this paper we propose a framework for dynamic conceptual clustering of web documents based on clusters of users that share common interests. The basic assumption is that the search results would be more relevant to a user when provided within the context of semantically related documents marked as `interesting' by a sufficiently large group of users with similar interests. This framework can support personalization of a search based on a search engine that `knows' the context of the user information needs and uses it to tailor the search results.