Tuning a Linguistic Information Retrieval System
نویسنده
چکیده
In this contribution a new interpretation of a symmetrical threshold semantics for a linguistic Information Retrieval Systems (IRS) is presented. It is modeled by means of a new linguistic matching function defined using a 2-tuple fuzzy linguistic approach. It softens the behaviour of symmetrical threshold semantics by processing in a more consistent way the query threshold weights, and in such a way, it allows a tuning of IRS. We show that its application in the evaluation of the weighted queries improves the retrieval results and the users’ satisfaction.
منابع مشابه
Tuning the matching function for a threshold weighting semantics in a linguistic information retrieval system
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