A novel non-functional matchmaking approach between fuzzy user queries and real world web services based on rough sets

• We propose in this paper a new matchmaking approach between user queries and real world Web services.
• It consists in generating fuzzy core classification rules of Web services to predefined categories.
• These rules leverage core attributes from the dataset, which are computed using rough sets theory.
• The fuzzy user query is then matched against the established core rules.
• The retrieved services are then ranked according to their distances to the user query.

We propose in this paper a novel matchmaking approach between fuzzy user queries and real world Web services. The matchmaking spans over a domain dependent classification step that produces fuzzy classification rules for Web services. The elaborated rules leverage a core set of non-functional quality attributes, which is extracted using rough sets theory. Furthermore, these rules are leveraged to classify Web services into categories, which allows reducing the matchmaking space. The experimental results show that our proposed matchmaking approach provides good results in terms of efficiency and precision.