An algorithm for matching contextualized schemas via SAT

The development of more and more complex distributed applications over large networks of computers has raised the problem of semantic inter-operability across autonomous applications. In this paper we propose an algorithm, called CTX-MATCH, for discovering semantic relations be-tween concepts belonging to heterogeneous and autonomously developed semantic schemas. The most significant innovations of the algorithm, which is theoretically founded on a well–known theory of contextual reasoning in AI, are that (i) the problem of finding relationships between concepts in different schemas is encoded as a problem of logical satisfiability (and so mappings have a well–defined semantic); and (ii) the way linguistic and domain knowledge is used to build the SAT problem. In this paper, we are mainly focused on the first aspect. The algorithm has been implemented as part of a peer-to-peer system for Distributed Knowledge Management, and tested on significant cases.