A composite approach to automating direct and indirect schema mappings

Automating schema mapping is challenging. Previous approaches to automating schema mapping focus mainly on computing direct matches between two schemas. Schemas, however, rarely match directly. Thus, to complete the task of schema mapping, we must also compute indirect matches. In this paper, we present a composite approach for generating a source-totarget mapping that contains both direct and many indirect matches between a source schema and a target schema. Recognizing expected-data values associated with schema elements and applying schema-structure heuristics are the key ideas needed to compute indirect matches. Experiments we have conducted over several real-world application domains show encouraging results, yielding about 90% precision and recall measures for both direct and indirect matches.

• Type: Journal
• Year: 2006
• Where: IS
• Authors: Li Xu, David W. Embley
• Keywords: Artificial Intelligence, Direct, Indirect Matches, IS 2006, Schema Mapping