A New Efficient Method for Calculating Similarity Between Web Services

TL;DR

This paper introduces a novel, more efficient method for measuring similarity between web services, addressing challenges in web service discovery and classification beyond traditional keyword and semantic approaches.

Contribution

The paper presents a new similarity measurement method that improves efficiency over existing techniques for classifying web services.

Findings

The proposed method outperforms traditional keyword-based approaches.

It offers better accuracy in web service classification.

The method reduces computational complexity in similarity calculations.

Abstract

Web services allow communication between heterogeneous systems in a distributed environment. Their enormous success and their increased use led to the fact that thousands of Web services are present on the Internet. This significant number of Web services which not cease to increase has led to problems of the difficulty in locating and classifying web services, these problems are encountered mainly during the operations of web services discovery and substitution. Traditional ways of search based on keywords are not successful in this context, their results do not support the structure of Web services and they consider in their search only the identifiers of the web service description language (WSDL) interface elements. The methods based on semantics (WSDLS, OWLS, SAWSDL...) which increase the WSDL description of a Web service with a semantic description allow raising partially this problem, but their complexity and difficulty delays their adoption in real cases. Measuring the similarity between the web services interfaces is the most suitable solution for this kind of problems, it will classify available web services so as to know those that best match the searched profile and those that do not match. Thus, the main goal of this work is to study the degree of similarity between any two web services by offering a new method that is more effective than existing works.