Substructure Discovery Using Minimum Description Length and Background Knowledge

TL;DR

This paper introduces an enhanced substructure discovery system, SUBDUE, based on the minimum description length principle, capable of identifying hierarchical, compressive, and conceptually meaningful substructures in structural data.

Contribution

The paper presents a new version of SUBDUE that incorporates background knowledge and approximate graph matching to improve substructure discovery and hierarchical data representation.

Findings

SUBDUE effectively compresses data by discovering meaningful substructures.

The system can incorporate background knowledge to guide discovery.

Experiments demonstrate SUBDUE's ability to find important structural concepts.

Abstract

The ability to identify interesting and repetitive substructures is an essential component to discovering knowledge in structural data. We describe a new version of our SUBDUE substructure discovery system based on the minimum description length principle. The SUBDUE system discovers substructures that compress the original data and represent structural concepts in the data. By replacing previously-discovered substructures in the data, multiple passes of SUBDUE produce a hierarchical description of the structural regularities in the data. SUBDUE uses a computationally-bounded inexact graph match that identifies similar, but not identical, instances of a substructure and finds an approximate measure of closeness of two substructures when under computational constraints. In addition to the minimum description length principle, other background knowledge can be used by SUBDUE to guide the search towards more appropriate substructures. Experiments in a variety of domains demonstrate SUBDUE's ability to find substructures capable of compressing the original data and to discover structural concepts important to the domain. Description of Online Appendix: This is a compressed tar file containing the SUBDUE discovery system, written in C. The program accepts as input databases represented in graph form, and will output discovered substructures with their corresponding value.