Graph indexing: a frequent structure-based approach
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A novel spectral coding in a large graph database
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Taming verification hardness: an efficient algorithm for testing subgraph isomorphism
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Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
TALE: A Tool for Approximate Large Graph Matching
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ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Mining graph patterns efficiently via randomized summaries
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Realistic, mathematically tractable graph generation and evolution, using kronecker multiplication
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An edge-based framework for fast subgraph matching in a large graph
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SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
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Efficient Multiview Maintenance under Insertion in Huge Social Networks
ACM Transactions on the Web (TWEB)
SQBC: An efficient subgraph matching method over large and dense graphs
Information Sciences: an International Journal
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Considerable efforts have been spent in studying subgraph problem. Traditional subgraph containment query is to retrieve all database graphs which contain the query graph g. A variation to that is to find all occurrences of a particular pattern(the query) in a large database graph. We call it subgraph matching problem. The state of art solution to this problem is GADDI. In this paper, we will propose a more efficient index and algorithm to answer subgraph matching problem. The index is based on the label distribution of neighbourhood vertices and it is structured as a multi-dimensional vector signature. A novel algorithm is also proposed to further speed up the isomorphic enumeration process. This algorithm attempts to maximize the computational sharing. It also attempts to predict some enumeration state is impossible to lead to a final answer by eagerly pruning strategy. We have performed extensive experiments to demonstrate the efficiency and the effectiveness of our technique.