Similarity Measure is a very important problem in Fuzzy Soft Set theory. In this paper, we have applied the notion of Distance and Similarity measures between two fuzzy soft set. First we discussed Decision making problem using fuzzy soft set based real life problems. Finally the similarity measures of normalized Hamming distance and normalized Euclidean distance have been applied to the proble...

The set of well defined and classified suspicious lesions regions from mammograms database are used as a reference pattern. The similarity measure for reference pattern image and patient mammogram is found by computing the distance between their corresponding feature vectors. The Euclidean distance metric is used to finding the nearest class to patient feature vector what in result mark the aut...

The weight is one of the most useful tools to measure the attribute importance when individuals make a decision or evaluate the alternatives. Among the methods which measure the weight, fuzzy measures is are subjective scales for the degrees of fuzziness and widely used to determine the degrees of subjective importance of evaluation items in numerous studies for the time being. The purpose of t...

Similarity measure is a very important problem in fuzzy soft set theory. In this paper, seven similarity measures of fuzzy soft sets are introduced, which are based on the normalized Hamming distance, the normalized Euclidean distance, the generalized normalized distance, the Type-2 generalized normalized distance, the Type-2 normalized Euclidean distance, the Hausdorff distance and the Chebysh...

A new concept of the inclusion measure for intuitionistic fuzzy sets is proposed by the axiomatic definition. Also, the distance measures, similarity measures and information entropy are recalled and summarized. Most of important, some relationships among distance measure, information entropy, and inclusion measure of IFSs are then investigated. Finally, we obtain some important theorems by whi...

Identification of cognates is an important component of computer assisted second language learning systems. We present a simple rule-based system to recognize cognates in English text from the perspective of the French language. At the core of our system is a novel similarity measure, orthographic edit distance, which incorporates orthographic information into string edit distance to compute th...

In many applications, it is necessary to determine the similarity of two strings. A widely-used notion of string similarity is the edit distance: the minimum number of insertions, deletions, and substitutions required to transform one string into the other. In this report, we provide a stochastic model for string edit distance. Our stochastic model allows us to learn a string edit distance func...

In this paper, first of all the distance measure entitled generalized Hausdorff distance is defined between two generalized fuzzy numbers that has been introduced by Chen [3]. Then using another distance and combining it with the generalized Hausdorff distance, a fuzzy distance measure is introduced with the help of fuzzy distance measure proposed in [1] to generalize fuzzy numbers. The concept...

A novel distance measure for distance-based speaker segmentation is proposed. This distance measure is nonparametric, in contrast to common distance measures used in speaker segmentation systems, which often assume a Gaussian distribution when measuring the distance betweentwo audio segments. This distance measure is essentially a k-nearestneighbor distance measure. Non-vowel segment removal in...

Melodic similarity is an important research topic in music information retrieval. The representation of symbolic music by means of trees has proven to be suitable in melodic similarity computation, because they are able to code rhythm in their structure leaving only pitch representations as a degree of freedom for coding. In order to compare trees, different edit distances have been previously ...