Abstract: Interval-valued fuzzy set (IVFS) is an extension of fuzzy set in which it presents a fuzzy set with an interval-valued membership. A similarity measure is a useful tool for determining the similarity degree between two objects. It is also an important measure for fuzzy concepts. In this paper, we propose a new similarity measure between IVFSs. Some properties of this similarity measur...

We show that a certain class of similarity measures, which is based on set-theoretic concepts, and explains many of the characteristics of human similarity assessment, can be interpreted as a distance in a suitable psychological space. This view unifies a number of different measures of similarity that psychological experiments have determined to be active in humans for different classes of sti...

in this paper, we present a revised similarity measure based onchen-and-chen's similarity measure for fuzzy risk analysis. the revisedsimilarity measure uses the corrected formulae to calculate the centre ofgravity points, therefore it is more  effective than the chen-and-chen'smethod. the revised similarity measure can overcome the drawbacks of theexisting methods. we have also proposed a new ...

We present a brief overview of the way in which image analysis, coupled with associated collateral text, is being used for auto-annotation and sentiment analysis. In particular, we describe our approach to auto-annotation using the graphtheoretic dominant set clustering algorithm and the annotation of images with sentiment scores from SentiWordNet. Preliminary results are given for both, and ou...

A well known fact is that every Lebesgue measurable set is regular, i.e., it includes an Fσ set of the same measure. We analyze this fact from a metamathematical or foundational standpoint. We study a family of Muchnik degrees corresponding to measure-theoretic regularity at all levels of the effective Borel hierarchy. We prove some new results concerning Nies’s notion of LR-reducibility. We bu...

This thesis mainly concerns itself with the issue of semantic similarity and computational applications of it. Semantic similarity has for a long time been a subject of intense scholarship in the fields of Artificial Intelligence, Psychology and Cognitive Science. Computational models trying to imitate aspects of this cognitive ability date back to Quillian and his spreading activation algorith...

recommender systems (rs) provide personalized recommendation according to user need by analyzing behavior of users and gathering their information. one of the algorithms used in recommender systems is user-based collaborative filtering (cf) method. the idea is that if users have similar preferences in the past, they will probably have similar preferences in the future. the important part of col...

How similar are two corpora? A measure of corpus similarity would be very useful for NLP for many purposes, such as estimating the work involved in porting a system from one domain to another. First, we discuss difficulties in identifying what we mean by ‘corpus similarity’: human similarity judgements are not finegrained enough, corpus similarity is inherently multidimensional, and similarity ...

Detecting outliers is an important task in many applications. Since most applications possess high dimensional data, traditional outlier detecting methods will become inefficient in such cases. To solve the problem, we propose the concept of outlying reduction by extending attribute reduction in rough set theory. Additionally, we define the key knowledge attribute subspace (KKAS), which can pro...