Semantic matching is finding a mapping between two knowledge representations encoded using the same ontology. Solving this matching problem is hard because the syntactic form of two knowledge representations rarely matches exactly. Previous research has shown transformation rules can be used to improve matching, but acquiring transformations is difficult. In this paper, we present an algorithm for mining transformation rules for semantic matching. This algorithm was evaluated in two domains -- battle space planning and chemistry. In both cases, the resulting transformations helped to improve matching significantly compared to using only taxonomic knowledge.

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In Proceedings of ECML/PKDD 2nd International Workshop on Mining Graphs, Trees and Sequences (MGTS'04) 2004.

@inproceedings{yeh:mgts04, title={Mining Transformation Rules for Semantic Matching}, author={Peter Yeh and Bruce Porter and Ken Barker}, booktitle={Proceedings of ECML/PKDD 2nd International Workshop on Mining Graphs, Trees and Sequences (MGTS'04)}, url="http://www.cs.utexas.edu/users/ai-lab?yeh:mgts04", year={2004} }