Database Normalization as a By-product of Minimum Message Length Inference
- Cite this paper as:
- Dowe D.L., Zaidi N.A. (2010) Database Normalization as a By-product of Minimum Message Length Inference. In: Li J. (eds) AI 2010: Advances in Artificial Intelligence. AI 2010. Lecture Notes in Computer Science, vol 6464. Springer, Berlin, Heidelberg
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 by-product) 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.
KeywordsMinimum Message Length MML Database Normalization Machine Learning Data Mining Intelligent Databases
Unable to display preview. Download preview PDF.