Combining artificial intelligence and databases for data integration

  • Authors:

  • Alon Y. Levy

  • Affiliations:

  • Department of Computer Science and Engineering, University of Washington, Seattle, Washington

  • Venue:
  • Artificial intelligence today
  • Year:
  • 1999

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Abstract

Data integration is a problem at the intersection of the fields of Artificial Intelligence and Database Systems. The goal of a data integration system is to provide a uniform interfacc to a multitude of data sources, whether they are within one enterprise or on the World-Wide Web. The key challenges in data integration arise because the data sources being integrated have been designed independently for autonomous applications, and their contents are related in subtle ways. As a result, a data integration system requires rich formalisms for describing contents of data sources and relating between contents of different sources. This paper discusses works aimed at applying techniques from Artificial Intelligence to the problem of data integration. In addition to employing Knowledge Representation techniques for describing contents of information sources, projects have also made use of Machine Learning techniques for extracting data from sources and planning techniques for query optimization. The paper also outlines future opportunities for applying AI techniques in the context of data integration.