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Efficient mining of top-k breaker emerging subgraph patterns from graph datasets

Version 2 2024-06-06, 11:28
Version 1 2014-11-20, 12:49
conference contribution
posted on 2024-06-06, 11:28 authored by M Gan, H Dai
This paper introduces a new type of discriminative subgraph pattern called breaker emerging subgraph pattern by introducing three constraints and two new concepts: base and breaker. A breaker emerging sub-graph pattern consists of three subpatterns: a con-strained emerging subgraph pattern, a set of bases and a set of breakers. An efficient approach is pro-posed for the discovery of top-k breaker emerging sub-graph patterns from graph datasets. Experimental re-sults show that the approach is capable of efficiently discovering top-k breaker emerging subgraph patterns from given datasets, is more efficient than two previ-ous methods for mining discriminative subgraph pat-terns. The discovered top-k breaker emerging sub-graph patterns are more informative, more discrim-inative, more accurate and more compact than the minimal distinguishing subgraph patterns. The top-k breaker emerging patterns are more useful for sub-structure analysis, such as molecular fragment analy-sis. © 2009, Australian Computer Society, Inc.

History

Volume

101

Pagination

183-191

Location

Melbourne, Vic.

Start date

2009-12-01

End date

2009-12-04

ISSN

1445-1336

ISBN-13

9781920682828

Language

eng

Publication classification

E Conference publication, E1.1 Full written paper - refereed

Copyright notice

2009, Australian Computer Society

Title of proceedings

AusDM 09 : Conferences in Research and Practice in Information Technology Series

Event

Australasian Data Mining. Conference (8th : 2009 : Melbourne, Vic.)

Publisher

Australian Computer Society

Place of publication

Crows Nest, N. S. W.

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