Towards Planning and Execution for Information Retrieval

The problem of information gathering has received considerable attention from the planning community in recent years. However, research in this area has generally assumed a user’s information goal is perfectly represented by the query, and typically adopts a relational database model for representing query operations and information sources. In this paper, we present a planning and execution framework intended to address the more general information retrieval (IR) problem in which queries are only approximate representations of the user’s true information goals, and complete models of the content of information sources are not available. Our approach reformulates traditional IR techniques such as synonym expansion and relevance-feedback as domain operators, explicitly modeling the uncertainty of action outcomes and of satisfying the user’s information needs, and taking into account resource constraints such as time. A forwardchaining planning and execution algorithm guides action selection, execution and replanning decisions using a userdefined utility function. We have implemented this approach in the INSPIRE (INtegrated System for Planning and Information REtrieval) architecture.

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