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Hierarchical Classifications with Attributes are tree-like structures used for organizing/classifying data. Due to the exponential growth and distribution of information across the network, and to the fact that such information is usually clustered by means of this kind of structures, we assist nowadays to an increasing interest in finding techniques to define mappings among such structures. In this paper, we propose a new algorithm for discovering mappings across hierarchical classifications, which faces the matching problem as a problem of deducing relations between sets of logical terms representing the meaning of hierarchical classification nodes. [ABSTRACT FROM AUTHOR] more...

One of the key challenges in the development of open semantic-based systems is enabling the exchange of meaningful information across applications which may use autonomously developed schemata. One of the typical solutions for that problem is the definition of a mapping between pairs of schemas, namely a set of point-to-point relations between the elements of different schemas. A lot of (semi-)automatic methods for generating such mappings have been proposed. In this paper we provide a preliminary investigation on the notion of correctness for schema matching methods. In particular we define different notions of soundness, strictly depending on what dimension (syntactic, semantic, pragmatic) of the language the mappings are defined on. Finally, we discuss some preliminary conditions under which a two different notions of soundness (semantic and pragmatic) can be related. [ABSTRACT FROM AUTHOR] more...

The development of more and more complex distributed applications over large networks of computers has raised the problem of semantic interoperability across applications based on local and autonomous semantic schemas (e.g., concept hierarchies, taxonomies, ontologies). In this paper we propose to view each semantic schema as a context (in the sense defined in [1]), and propose an algorithm for automatically discovering relations across contexts (where relations are defined in the sense of [7]). The main feature of the algorithm is that the problem of finding relationships between contexts is encoded as a problem of logical satisfiability, and so the discovered mappings have a well-defined semantic. The algorithm we describe has been implemented as part of a peer-to-peer system for Distributed Knowledge Management, and tested on significant cases. [ABSTRACT FROM AUTHOR] more...