Graph-Based Data Mining

Graph-Based Data Mining

Lawrence B. Holder (University of Texas at Arlington, USA) and Diane J. Cook (University of Texas at Arlington, USA)
Copyright: © 2005 |Pages: 6
DOI: 10.4018/978-1-59140-557-3.ch102
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Abstract

Graph-based data mining represents a collection of techniques for mining the relational aspects of data represented as a graph. Two major approaches to graph-based data mining are frequent subgraph mining and graph-based relational learning. This article will focus on one particular approach embodied in the Subdue system, along with recent advances in graph-based supervised learning, graph-based hierarchical conceptual clustering, and graph-grammar induction.

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