Preference and Similarity-based Behavioral Discovery of Services

We extend Constraint Automata by replacing boolean constraints with semiring-based soft constraints. The obtained general formal tool can be used to represent preference-based and similarity-based queries, which allow a user more freedom in choosing the behavior of the service to finally use, among all possible choices. A user states his preferences through a “soft” query, and obtains results that satisfy this query with different levels of preference. The soft requirements may involve a parameter data of the service operations, or the (names of the) operations themselves. Moreover, we introduce a first implementation of the search procedure by using declarative (Soft) Constraint Programming

Semantic Web Services Discovery Regarded as a Constraint Satisfaction Problem

International audienceThe web services discovery is a fundamental problem in semantic web services. The problem is to find services that can be combined to form an admissible answer to a query. At the same time, constraint satisfaction is recognized as a fundamental problem in artificial intelligence. In this paper, we will investigate the connection between both problems. We will show that they are the same problem despite their very different formulation. The reason is that they can be recast as the following fundamental algebraic problem: given two relational structures A and B, is there a homomorphism h:A→ B? In our approach, the proposed homomorphism is a labelled graph homomorphism. The latter is based on simple conceptual graph which is considered as the kernel of most knowledge representation formalism built upon Sowa’s model. Reasoning in this model can be expressed by a graph homomorphism