article

State of the art of graph-based data mining

Authors:

Takashi Washio,

Hiroshi MotodaAuthors Info & Claims

ACM SIGKDD Explorations Newsletter, Volume 5, Issue 1

Pages 59 - 68

https://doi.org/10.1145/959242.959249

Published: 01 July 2003 Publication History

Abstract

The need for mining structured data has increased in the past few years. One of the best studied data structures in computer science and discrete mathematics are graphs. It can therefore be no surprise that graph based data mining has become quite popular in the last few years.This article introduces the theoretical basis of graph based data mining and surveys the state of the art of graph-based data mining. Brief descriptions of some representative approaches are provided as well.

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State of the art of graph-based data mining

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Published In

cover image ACM SIGKDD Explorations Newsletter

ACM SIGKDD Explorations Newsletter Volume 5, Issue 1

July 2003

101 pages

ISSN:1931-0145

EISSN:1931-0153

DOI:10.1145/959242

Issue’s Table of Contents

Copyright © 2003 Authors.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 July 2003

Published in SIGKDD Volume 5, Issue 1

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Paldino GLebichot BLe Borgne YSiblini WOblé FBoracchi GBontempi G(2024)The role of diversity and ensemble learning in credit card fraud detectionAdvances in Data Analysis and Classification10.1007/s11634-022-00515-518:1(193-217)Online publication date: 1-Mar-2024
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Chen QChen Q(2024)Association Analysis: Basic Concepts and AlgorithmsAssociation Analysis Techniques and Applications in Bioinformatics10.1007/978-981-99-8251-6_2(9-53)Online publication date: 26-Apr-2024
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