In the fuzzy set theory, information  measures play a paramount role in several areas such as decision making, pattern recognition etc. In this paper, similarity measure based on cosine function and entropy measures based on logarithmic function for IFSs are proposed. Comparisons of proposed similarity and entropy measures with the existing ones are listed. Numerical results limpidly betoken th...

We present CoSimRank, a graph-theoretic similarity measure that is efficient because it can compute a single node similarity without having to compute the similarities of the entire graph. We present equivalent formalizations that show CoSimRank’s close relationship to Personalized PageRank and SimRank and also show how we can take advantage of fast matrix multiplication algorithms to compute C...

Risk analysis plays an important role in many application systems. The current researches prefer to use fuzzy set theory for risk analysis. In this paper, we present a new fuzzy risk analysis method based on generalized fuzzy numbers. Firstly, we define new arithmetic operations between generalized fuzzy numbers. Then, we propose a new method to measure the degree of similarity between generali...

Asmhan Flieh Hassan, Dong Cai-lin and Zahir M. Hussain PhD Candidate, School of Mathematics and Statistics, HuaZhong Normal University, 152 Luoyu Road, Wuhan, 430079, China Department of Mathematics University of Kufa, Najaf, Iraq School of Mathematics and Statistics, HuaZhong Normal University, 152 Luoyu Road, Wuhan, 430079, China Department of Computer Science, University of Kufa, Najaf, Iraq...

This paper aims at introducing a new dissimilarity measure for categorical objects into an extension of k-representative algorithm for clustering categorical data. Basically, the proposed dissimilarity measure is based on an information theoretic definition of similarity introduced by Lin [15] that considers the amount of information of two values in the domain set. In order to demonstrate the ...