A Hybrid Approach to Recommending Semantic Software Services

The current proliferation of software services means users should be supported when selecting one service out of the many which meet consumer´s needs. Recommender Systems provide such support for selecting products, yet their direct application to software services is not straightforward. In this paper, we derive three requirements for software service recommender systems and then propose a hybrid recommendation approach to address these requirements and provide effective recommendations in conditions of scarce user feedback. The approach combines semantic Content-based reasoning and context-dependent Collaborative Filtering. The paper ends with the experiments based on a realistic set of semantic services against existing approaches, demonstrating how our approach can produce effective recommendation using semantic reasoning over service specifications.