Network querying is a growing domain with vast applications ranging from screening compounds against a database of known molecules to matching sub-networks across species. Graph indexing is a powerful method for searching a large database of graphs. Most graph indexing methods to date tackle the exact matching (isomorphism) problem, limiting their applicability to specific instances in which such matches exist. Here we provide a novel graph indexing method to cope with the more general, inexact matching problem. Our method, SIGMA, builds on approximating a variant of the set-cover problem that concerns overlapping multi-sets. We extensively test our method and compare it to a baseline method and to the state-of-the-art Grafil. We show that SIGMA outperforms both, providing higher pruning power in all the tested scenarios.

SIGMA: A SET-COVER-BASED INEXACT GRAPH MATCHING ALGORITHM

MONGIOVI', MISAEL;PULVIRENTI, ALFREDO;FERRO, Alfredo;
2010

Abstract

Network querying is a growing domain with vast applications ranging from screening compounds against a database of known molecules to matching sub-networks across species. Graph indexing is a powerful method for searching a large database of graphs. Most graph indexing methods to date tackle the exact matching (isomorphism) problem, limiting their applicability to specific instances in which such matches exist. Here we provide a novel graph indexing method to cope with the more general, inexact matching problem. Our method, SIGMA, builds on approximating a variant of the set-cover problem that concerns overlapping multi-sets. We extensively test our method and compare it to a baseline method and to the state-of-the-art Grafil. We show that SIGMA outperforms both, providing higher pruning power in all the tested scenarios.
Indexing Methods; graph matching; network querying
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11769/251702
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