Semantic Schema Matching | Zendy

Fausto Giunchiglia | Zendy; Pavel Shvaiko | Zendy; Mikalai Yatskevich | Zendy

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Semantic Schema Matching

Author(s) -

Fausto Giunchiglia,

Pavel Shvaiko,

Mikalai Yatskevich

Publication year - 2005

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-29736-7

DOI - 10.1007/11575771_23

Subject(s) - computer science , schema matching , xml , semantic matching , schema (genetic algorithms) , semantic equivalence , information retrieval , star schema , semantic computing , semantic similarity , pattern matching , theoretical computer science , matching (statistics) , document structure description , artificial intelligence , natural language processing , data mining , semantic web , data integration , world wide web , mathematics , statistics

We view match as an operator that takes two graph-like structures (e.g., XML schemas) and produces a mapping between the nodes of these graphs that correspond semantically to each other. Se- mantic schema matching is based on the two ideas: (i) we discover map- pings by computing semantic relations (e.g., equivalence, more general); (ii) we determine semantic relations by analyzing the meaning (con- cepts, not labels) which is codified in the elements and the structures of schemas. In this paper we present basic and optimized algorithms for semantic schema matching, and we discuss their implementation within the S-Match system. We also validate the approach and evaluate S-Match against three state of the art matching systems. The results look promis- ing, in particular for what concerns quality and performance.

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