Representing User Information Context with Ontologies

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, we propose a framework for contextualized information access that seamlessly combines these elements in order to effectively locate and provide the most appropriate result for users' information needs. In particular, we focus on integrating a user's query with semantic knowledge from an existing concept hierarchy to assist the user in information retrieval. In our framework, the user’s “context” is captured via nodes in a concept lattice induced from the original ontology and is updated incrementally based on user's interactions with the concepts in the ontology. Our experimental results show that utilizing the user context improves the effectiveness of the search queries, especially in the typical case of Web users who tend to use very short queries.

[1]  Steven L. Lytinen,et al.  Concept Based Query Enhancement in the ARCH Search Agent , 2003, International Conference on Internet Computing.

[2]  Henry Lieberman,et al.  Autonomous interface agents , 1997, CHI.

[3]  T. Joachims.  WebWatcher : A Tour Guide for the World Wide Web , 1997 .

[4]  Jaime Teevan,et al.  Implicit feedback for inferring user preference: a bibliography , 2003, SIGF.

[5]  Vipin Kumar,et al.  Document Categorization and Query Generation on the World Wide Web Using WebACE , 1999, Artificial Intelligence Review.

[6]  Jay Budzik,et al.  Supporting on-line resource discovery in the context of ongoing tasks with proactive software assistants , 2002, Int. J. Hum. Comput. Stud..

[7]  James Allan,et al.  Incremental relevance feedback for information filtering , 1996, SIGIR '96.

[8]  James Allan,et al.  The effect of adding relevance information in a relevance feedback environment , 1994, SIGIR '94.

[9]  Amanda Spink,et al.  U.S. versus European web searching trends , 2002, SIGF.

[10]  Robin Burke,et al.  USING CONCEPT HIERARCHIES TO ENHANCE USER QUERIES IN WEB-BASED INFORMATION RETRIEVAL , 2003 .

[11]  Susan T. Dumais,et al.  SIGIR 2003 workshop report: implicit measures of user interests and preferences , 2003, SIGF.

[12]  Michael McGill,et al.  Introduction to Modern Information Retrieval , 1983 .

[13]  Thorsten Joachims,et al.  Web Watcher: A Tour Guide for the World Wide Web , 1997, IJCAI.

[14]  Djoerd Hiemstra,et al.  Challenges in information retrieval and language modeling: report of a workshop held at the center for intelligent information retrieval, University of Massachusetts Amherst, September 2002 , 2003, SIGF.