Fuzzy-based approach for context-aware service retrieval

The idea presented in paper is inspired from the wide prospect given by the integration of fuzzy sets and linguistic quantifiers in the modeling of context and quantification of similarities measurement. In pervasive services retrieval, dealing with context in a flexible and efficient way is extremely important. In this paper we propose a practical classification of context into functional and non functional context. We use the first type in the service discovery with an ontology based model supporting fuzzy context predicates and fuzzy reasoning, while the second type is used for the best-fitting service selection based on the linguistic quantifier “almost all”. Finally, the listed scenario example illustrates the realization and the effectiveness of our approach.