This study explored the use of context-aware recommender system to facilitate web service composition. The needs for composition of existing web services to generate functionality for users are increasing. And an intelligent framework is needed to alleviate users' burden to discover, select, invoke and combine web services. In this study, we focus on using context-aware recommender system to provide users with the most appropriate web services composition. The concept of context-aware collaborative filtering is used here to learn and predict user preferences, and based on this information, to compose necessary web services to achieve user request. We provide a restaurant recommender system prototype for the restaurant search scenario to demonstrate how proposed architecture works.
Proceeding of The Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp.227-229