AAAI Publications, Twenty-First IAAI Conference

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Enabling Data Quality with Lightweight Ontologies
Clint R. Bidlack

Last modified: 2009-04-09


As the volume and interconnectedness of corporate data grows, data quality is becoming a business competency essential to success. Existing methods for managing data quality do not scale up to large volumes of data in a way that is directly manageable by the owner of the data. For the past two years a new breed of data quality products, built on applied AI techniques, are empowering non-technical users. Over 150 businesses are benefiting from these products including NASDAQ, Visa, Experian, Oracle, Fidelity, Bank of America, Volvo, Dell, Sabic, and Dassault Systems. The applied AI techniques described include lightweight ontologies to efficiently find inexact textual matches in large data sets.


ontologies, domain knowledge, inexact matching

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