A new method to handle problems of Information Retrieval (IR) and related applications is proposed. The method is based on Fuzzy Interval Numbers (FINs) introduced in fuzzy system applications. Definition, interpretation and a computation algorithm of FINs are presented. The frame of use FINs in IR is given. An experiment showing the anticipated importance of these techniques in Cross Language ...

Traditional statistical tools for performing regression cannot handle the large uncertainties present in a fuzzy number dataset. Therefore we will have to rely on techniques developed for interval analysis (Moore 1966; Moore 1979). A useful property of algorithms that handle fuzzy numbers is that they can be rewritten in terms of intervals allowing the powerful mathematical tools of interval an...

In the traditional fuzzy logic, the expert’s degree of certainty in a statement is described either by a number from the interval [0, 1] or by a subinterval of such an interval. To adequately describe the opinion of several experts, researchers proposed to use a union of the corresponding sets – which is, in general, more complex than an interval. In this paper, we prove that for such set-value...

Interval-valued intuitionistic fuzzy number uses membership degree and non-member ship degree to express a decision-maker’s hesitation, which make decision-maker express his/her opinion in uncertainty decision-making environment easily. The comparison between some intervalvalued intuitionistic fuzzy numbers can not be undertaken because of its limitation. In application such as weak consistency...

In this paper, we first use a fuzzy preference relation with a membership function representing preference degree forcomparing two interval-valued fuzzy numbers and then utilize a relative preference relation improved from the fuzzypreference relation to rank a set of interval-valued fuzzy numbers. Since the fuzzy preference relation is a total orderingrelation that satisfies reciprocal and tra...