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Adapting a diagnostic problem-solving model to information retrieval
2000
Information Processing & Management
In this paper, a competition-based connectionist model for diagnostic problem-solving is adapted to information retrieval. In this model, we treat documents as \disorders" and user information needs as \manifestations", and a competitive a c t i v ation mechanism is used which converges to a set of documents that best explain the given user information needs. By combining the ideas of Bayesian inferencing and diagnostic inferencing using parsimonious covering theory, this model removes many di
doi:10.1016/s0306-4573(99)00037-0
fatcat:lvvn4o64l5blxedtc253m4kkxy