Publication

MARGIN: Maximal frequent subgraph mining

2010
Journal Articles

Abstract

The exponential number of possible subgraphs makes the problem of frequent subgraph mining a challenge. The set of maximal frequent subgraphs is much smaller to that of the set of frequent subgraphs providing ample scope for pruning. MARGIN is a maximal subgraph mining algorithm that moves among promising nodes of the search space along the “border” of the infrequent and frequent subgraphs. This drastically reduces the number of candidate patterns in the search space. The proof of correctness of the algorithm is presented. Experimental results validate the efficiency and utility of the technique proposed.

Official source

https://infoscience.epfl.ch/entities/publication/2a35c489-c95e-467b-acea-bac2f7bbee2e

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2010
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/2a35c489-c95e-467b-acea-bac2f7bbee2e

About this result

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In theoretical computer science, the subgraph isomorphism problem is a computational task in which two graphs G and H are given as input, and one must determine whether G contains a subgraph that is isomorphic to H. Subgraph isomorphism is a generalization of both the maximum clique problem and the problem of testing whether a graph contains a Hamiltonian cycle, and is therefore NP-complete. However certain other cases of subgraph isomorphism may be solved in polynomial time.

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