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Every user has a distinct background and a specific goal when searching for information on the Web. The goal of Web search personalization is to tailor search results to a particular user based on that user's interests and preferences. Effective personalization of information access involves two important challenges: accurately identifying the user context(More)
The effectiveness of Internet search engines is often hampered by the ambiguity of user queries and the reluctance or inability of users to build less ambiguous multi-word queries. Our system, ARCH, is a client-side Web agent, which incorporates domain-specific concept hierarchies together with interactive query formulation in order to automatically produce(More)
—Every user has a distinct background and a specific goal when searching for information on the Web. The goal of Web search personalization is to tailor search results to a particular user based on that user's interests and preferences. Effective personalization of information access involves two important challenges: accurately identifying the user(More)
Collaborative recommendation is effective at representing a user's overall interests and tastes, and finding peer users that can provide good recommendations. However, it remains a challenge to make collaborative recommendation sensitive to a user's specific context and to the changing shape of user interests over time. Our approach to building(More)
The critical elements that make up a user's information context include the user profiles that reveal long-term interests and trends, the short-term information need as might be expressed in a query, and the semantic knowledge about the domain being investigated. The next generation of intelligent information agents, that can seamlessly integrate these(More)
The quality of the search experience has been an enduring problem for the World Wide Web. One of the well-known difficulties is the tendency of users to use short, under-specified and ambiguous queries, which tend to retrieve large amounts of irrelevant material. Traditional query expansion and relevance feedback approaches have been used to address this(More)
The goal of Web search personalization is to tailor search results to a particular user based on that user's interests and preferences. We present an approach to personalized search that involves building models of user context as ontological profiles by assigning implicitly derived interest scores to existing concepts in a domain ontology. Our experiments(More)
One of the key factors for accurate and effective information access is the user context. The critical elements that make up a user's information context include the semantic knowledge about the domain being investigated, the short-term information need as might be expressed in a query, and the user profiles that reveal long-term interests. In this paper,(More)
One of the key factors for effective personalization of information access is the user context. We propose a framework which integrates several critical elements that make up the user context, namely, the user's short-term behavior, semantic knowledge from ontologies that provide explicit representations of the domain of interest, and long-term user(More)