Selecting Task-Relevant Sources for Just-in-Time Retrieval
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David B. Leake, Larry Birnbaum, Cameron Marlow, and Hao Yang. Proceedings of the AAAI-99 Workshop on Exploring Synergies of Knowledge Management and Case-Based Reasoning. AAAI Press, Menlo Park, 1999. 5 pages.


``Just-in-time'' information systems monitor their users' tasks, anticipate task-based information needs, and proactively provide their users with relevant information. The effectiveness of such systems depends both on their capability to track user tasks and on their ability to retrieve information that satisfies task-based needs. The Watson system \cite{budzik-et-al98,budzik-hammond99} provides a framework for monitoring user tasks and identifying relevant content areas, and uses this information to generate focused queries for general-purpose search engines and for specialized search engines integrated into the system. The proliferation of specialized search engines and information repositories on the Web provides a rich source of additional information pre-focused for a wide range information needs, potentially enabling just-in-time systems to exploit that focus by querying the most relevant sources. However, putting this into practice depends on having general scalable methods for selecting the best sources to satisfy the user's needs. This paper describes early research on augmenting Watson with a general-purpose capability for automatic information source selection. It presents a source selection method that has been integrated into Watson and discusses general issues and research directions for task-relevant source selection.

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