On inference rules of logic-based information retrieval systems

摘要

Relevance of the retrieved documents to a query is in the sense of information retrieval a judgement of the user rather than the material implication in the sense of logic. In this paper we depart from deductive paradigm with object-oriented extensions, then relax the too strict modus ponens in the classic propositional logic by appropriate inference rules that would capture the relevance of information in the document to the information needed by the user. In such a framework, a document is relevant to a query if the latter can be deduced from the set of axioms associated with the document using inference rules. As various kinds of inference rules will be used in the deduction, we distinguish between logical, strict, and plausible rules. Answering a query in such a framework can be done either by a special query processor that supports different kinds of inference mechanisms, or by relaxing the original query so that it can be evaluated by an ordinary query processor. Instead of suggesting a new logic model, we make use of the query answering machinery of deductive and object-oriented database in this approach.