The minimum description length principle for pattern mining (MDL4PM).

Abstract: Considering that patterns express the repeated presence in the data of particular items, attribute values or other discrete properties, mining patterns is a core task in data analysis. Beyond issues of efficient enumeration, the selection of patterns constitutes a major challenge. The MDL principle, a model selection method grounded in information theory, has been applied to pattern mining with the aim to obtain compact high-quality sets of patterns. After introducing some necessary concepts to formalise the pattern mining task, we will review MDL-based methods for mining various types of data and patterns and try to highlight their common characteristics and differences. Finally, we will discuss some of the issues regarding these methods, and highlight currently active related data analysis problems.

Computer scienceMathematics

Audience: researchers in the discipline

( paper )

Seminar on Algorithmic Aspects of Information Theory

Series comments: This online seminar is a follow up of the Dagstuhl Seminar 22301, www.dagstuhl.de/en/program/calendar/semhp/?semnr=22301.