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Efficient Mining of Top-k Breaker Emerging Subgraph Patterns from Graph Datasets

Gan, M. and Dai, H.

    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 constrained emerging subgraph pattern, a set of bases and a set of breakers. An efficient approach is proposed for the discovery of top-k breaker emerging sub-graph patterns from graph datasets. Experimental results show that the approach is capable of efficiently discovering top-k breaker emerging subgraph patterns from given datasets, is more efficient than two previous methods for mining discriminative subgraph patterns. The discovered top-k breaker emerging sub-graph patterns are more informative, more discriminative, 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 analysis.
Cite as: Gan, M. and Dai, H. (2009). Efficient Mining of Top-k Breaker Emerging Subgraph Patterns from Graph Datasets. In Proc. Eighth Australasian Data Mining Conference (AusDM`09) Melbourne, Australia. CRPIT, 101. Kennedy P. J., Ong K. and Christen P. Eds., ACS. 183-192
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