Different interpretations of fuzzy gradual-inclusion-based IR models

Abstract

Recently, a theoretical fuzzy IR system, based on gradual inclusion measures, has been proposed [1]. In this model, derived from the division of fuzzy relations, the gradual inclusion of a query in a document is modeled by a fuzzy implication. In previous papers, we have shown that, under some assumptions, this model can be seen as a Vector Space Model. This paper also studies other interpretations of our fuzzy IR models based on gradual inclusions. It is shown that the fuzzy models can be interpreted as language models for IR. The links with logical models to IR are also recalled. More generally, this paper discusses the links between these models, shown from the point of view of our fuzzy models.

A Belief-Based Approach to Measuring Message Acceptability

“…The intuitive meaning of this is that incoming information is relevant to a domain if the models of the formula describing the domain are included in the models of the formula describing incoming information. However, because entailment is too rigid a relation and cannot express partial relevance [15], what we propose is in line with fuzzy set-based models in Information retrieval [29], where one resorts to a fuzzy measure of the χ d |= φ entailment. We define one such measure based on possibilistic conditioning [4] of φ by χ d .…”