An Algorithm for Subgraph Isomorphism
Journal of the ACM (JACM)
Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
Communications of the ACM
Structural Matching in Computer Vision Using Probabilistic Relaxation
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Mobile Computing
Reachability and Distance Queries via 2-Hop Labels
SIAM Journal on Computing
Graph indexing: a frequent structure-based approach
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
A (Sub)Graph Isomorphism Algorithm for Matching Large Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Closure-Tree: An Index Structure for Graph Queries
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Fast best-effort pattern matching in large attributed graphs
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
GADDI: distance index based subgraph matching in biological networks
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Graph-based mining of multiple object usage patterns
Proceedings of the the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Distance-join: pattern match query in a large graph database
Proceedings of the VLDB Endowment
On graph query optimization in large networks
Proceedings of the VLDB Endowment
Efficient algorithms for generalized subgraph query processing
Proceedings of the 21st ACM international conference on Information and knowledge management
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In recent years, pattern matching has been an important graph analysis tool in various applications. In previous existing models, each edge in the query pattern represents the same relationship, e.g., the two endpoint vertices have to be connected or the distance between them should be within a certain uniform threshold. However, various real world applications may require edges representing different relationships or distances, some may be longer while others may be shorter. Therefore, we introduce the flexible pattern matching model where a range [mine, maxe] is associated with an edge e in the query pattern, which means that the minimum distance between the matched endpoints of e is in the range of [mine,maxe]. A novel pattern matching algorithm utilizing two types of indices is devised. In addition to the traditional pattern matching scheme, a top-k matches generation model is also proposed. Extensive empirical studies have been conducted to show the effectiveness and efficiency of our indices and methods.