Database Normalization as a By-product of Minimum Message Length Inference

Database normalization is a central part of database design in which we re-organise the data stored so as to progressively ensure that as few anomalies occur as possible upon insertions, deletions and/or modifications. Successive normalizations of a database to higher normal forms continue to reduce the potential for such anomalies. We show here that database normalization follows as a consequence (or special case, or byproduct) of the Minimum Message Length (MML) principle of machine learning and inductive inference. In other words, someone (previously) oblivious to database normalization but well-versed in MML could examine a database and - using MML considerations alone - normalise it, and even discover the notion of attribute inheritance.

• Type: Journal
• Year: 2010
• Where: AUSAI
• Authors: David L. Dowe, Nayyar Abbas Zaidi
• Keywords: Artificial Intelligence, AUSAI 2010, Database, Database Design, Database Normalization