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Intelligent information retrieval: diagnosing information need. : Part I. The theoretical framework for developing an intelligent IR tool
Authors:Charles Cole
Institution:Communication Studies, Concordia University, 7141 Sherbrooke St. West, BR-111, Montreal, Qc., H4B 1R6, Canada
Abstract:The research examines the notion that the principles underlying the procedure used by doctors to diagnose a patient's disease are useful in the design of “intelligent” IR systems because the task of the doctor is conceptually similar to the computer (or human) intermediary's task in “intelligent information retrieval”: to draw out, through interaction with the IR system, the user's query/information need. The research is reported in two parts. In Part II, an information retrieval tool is described which is based on “intelligent information retrieval” assumptions about the information user. In Part I, presented here, the theoretical framework for the tool is set out. This framework is borrowed from the diagnostic procedure currently used in medicine, called “differential diagnosis”. Because of the severe consequences that attend misdiagnosis, the operating principle in differential diagnosis is (1) to expand the uncertainty in the diagnosis situation so that all possible hypotheses and evidence are considered, then (2) to contract the uncertainty in a step by step fashion (from an examination of the patient's symptoms, through the patient's history and a physical (signs), to laboratory tests). The IR theories of Taylor, Kuhlthau and Belkin are used to demonstrate that these medical diagnosis procedures are already present in IR and that it is a viable model with which to design “intelligent” IR tools and systems.
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