Eyal Shlomo Shimony

Senior Academic

Probabilistic model for schema understanding and matching

Schema matching is the problem of finding a correspondence between schemas - relational database schemas or web repositories. The ad-hoc approaches perform poorly on real-world schemas due to the abundance of non-dictionary abbreviations. Our approach to schema matching is based on deep understanding of the schema, using an integrative probabilistic generative model as a frame-work for comparing candidate interpretations. In empirical evaluation, the proposed model performed well in interpreting relational schemas, and exhibited high resistance to noise in the model parameters.

Publication language English
Pages 4768-4773
Publication status Published - 01.12.2004

ASJC Scopus subject areas

General Engineering
Access to Document
10.1109/ICSMC.2004.1401285
Other files and links
Link to publication in Scopus