A Measure Standard for Ontology-Based Service Recommendation

Abstract

Web Service is becoming the next generation of web-based application. With enhancement of quality of services and increasing quantity of services, how to recommend the suitable services according to personalized requirement becomes an urgent question. In the existing approaches of service recommendation, the result of service recommendation is the service list in which there is no evaluation standard that we can use to distinguish services with high relevancy and low relevancy. So in real-world, the user may obtain low relative services. To address the problem, in this paper, membership function is analyzed and recommendation measure standard is proposed. With dynamic programming theory, an ontology based approach of service recommendation is provided. In the result of service recommendation, membership as measure index is used to divide high relative services, medium relative services and low relative services. High relative services are recommended to the user. So the recommended services are accurate and available.