Importance in knowledge systems

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In knowledge systems, pieces of information (evidence, hypotheses, attributes, terms, documents, rules) are usually assumed to carry equal importance and to be independent of each other, although it might not actually be the case. Issues for a logic of weighted queries, with possibility of also weighting documents and logical connectors (in terms of intelligent retrieval, for example) are presented here, using “min” or t-norms, and soft operators involving p-norms. This logic cannot be a conventional one for, when introducing relative importance between concepts, definitions are different for ANDed and ORed weighted queries. A concept of “nought”, a limit case of no-importance queries, and its behaviour with fuzzy sets operations is developed, in particular the notion of an extended membership is introduced. Finally it is shown, with a biomedical example, how to combine importance with soft matching in rule-based systems.

论文关键词:Knowledge systems,information retrieval,weighted queries,importance,fuzzy sets,t-norms,soft operators,nought,soft matching

论文评审过程:Received 11 August 1989, Available online 10 June 2003.

论文官网地址:https://doi.org/10.1016/0306-4379(89)90013-6