Anzeige
Erschienen in:
2015 | OriginalPaper | Buchkapitel
The Difference and the Norm — Characterising Similarities and Differences Between Databases
verfasst von : Kailash Budhathoki, Jilles Vreeken
Erschienen in: Machine Learning and Knowledge Discovery in Databases
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Suppose we are given a set of databases, such as sales records over different branches. How can we characterise the differences and the norm between these datasets? That is, what are the patterns that characterise the general distribution, and what are those that are important to describe the individual datasets? We study how to discover these pattern sets simultaneously and without redundancy – automatically identifying those patterns that aid describing the overall distribution, as well as those pointing out those that are characteristic for specific databases. We define the problem in terms of the Minimum Description Length principle, and propose the
DiffNorm
algorithm to approximate the MDL-optimal summary directly from data. Empirical evaluation on synthetic and real-world data shows that
DiffNorm
efficiently discovers descriptions that accurately characterise the difference and the norm in easily understandable terms.