A Survey on Web Service Mining by Collaborative Filtering and QoS

Web service mining has become one of the promising areas of Service Oriented Architecture. Web service discovery methods include syntactic based system and semantic based system. Recommender system plays a vital role in recommending a product to customer, seldom used for web service recommendation. A variety of techniques have been proposed for performing recommendation namely, content-based, collaborative, demographic-based and other techniques. To improve performance these techniques has been combined in hybrid recommendation system. The most widely used filtering technique of recommender system is collaborative filtering. In this paper, we describe various collaborative filtering by QoS rating techniques applied to web service mining and addresses various collaborative filtering problems namely, cold-start problem, gray sheep problem, synonym problem, ramp-up problem, shilling attack, data sparsity and scalability. Keywords— Web service mining, Service Oriented Architecture, Recommender system, Collaborative Filtering, QoS.