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Graph-Based Data Mining
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Author(s): Lawrence B. Holder (University of Texas at Arlington, USA)and Diane J. Cook (University of Texas at Arlington, USA)
Copyright: 2005
Pages: 6
Source title:
Encyclopedia of Data Warehousing and Mining
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
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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