Measure of Similarity between Fuzzy Concepts for Optimization of Fuzzy Semantic Nets

TL;DR

This paper introduces a method to measure similarity between fuzzy concepts to optimize semantic networks, aiming to reduce search time and improve user-object and goal identification efficiency.

Contribution

It proposes a novel similarity measure for fuzzy concepts to enhance the optimization of semantic networks in user-object and goal searches.

Findings

Reduces search time in semantic networks

Improves accuracy in identifying relevant objects and goals

Optimizes the process of matching fuzzy concepts

Abstract

This paper presents a method to measure the similarity between different fuzzy concepts in order to optimize Semantic networks. The problem approached is the minimization of the time of research and identification of user's Objects and Goals. Indeed, it concerns to determine to each instant the totality of Objects (respectively Goals) among which one can identify rapidly the most satisfactory for the user's Object and Goal. Alone Objects and most similar Goals to Objects and researched Goals of the viewpoint of attribute values will be processed, what will avoid the analysis of all Objects and system Goals far of needs of the user.