In this paper we have introduced the concept of cosine similarity measures for neutrosophic soft set and interval valued neutrosophic soft set.An application is given to show its practicality and effectiveness.

In this paper, we have defined different types of similarity measures between Neutrosophic Soft (NS) sets and studied some of their properties. Finally we have solve a real life problem by using similarity measure of neutrosophic soft sets.

In this work we use the concept of a ’n’-valued refined neutrosophic soft sets and its properties to solve decision making problems. Also asimilarity measure between two’n’valued refined neutrosophic soft sets are proposed.

Similarity measure is an important tool in multiple criteria decision-making problems, which can be used to measure the difference between the alternatives. In this paper, some new similarity measures of single-valued neutrosophic sets (SVNSs) and interval-valued neutrosophic sets (IVNSs) are defined based on the Euclidean distance measure, respectively, and the proposed similarity measures satisfy the axiom of the similarity measure. Furthermore, we apply the proposed similarity measures to medical diagnosis decision problem; the numerical example is used to illustrate the feasibility and effectiveness of the proposed similarity measures of SVNSs and IVNSs, which are then compared to other existing similarity measures.

The primary focus of this manuscript comprises three sections. Initially, we introduce the concept of a simplified intuitionistic neutrosophic soft set. We impose an intuitionistic condition between the membership value soft truth and falsity such that their sum does not exceed unity.

In this paper, we define a rough cosine similarity measure between two rough neutrosophic sets. The notions of rough neutrosophic sets (RNS) will be used as vector representations in 3D-vector space. The rating of all elements in RNS is expressed with the upper and lower approximation operator and the pair of neutrosophic sets which are characterized by truth-membership degree, indeterminacy-membership degree, and falsity-membership degree. A numerical example of the medical diagnosis is provided to show the effectiveness and flexibility of the proposed method.

In this paper we propose the three types of similarity measures between fuzzy neutrosophic soft sets based on value matrix of fuzzy neutrosophic soft sets. Furthermore, we demonstrate the efficiency of the proposed similarity measures through the application in decision making.