Algorithmics and applications of tree and graph searching
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Finding Interesting Associations without Support Pruning
IEEE Transactions on Knowledge and Data Engineering
Subgraph Isomorphism Detection in Polynominal Time on Preprocessed Model Graphs
ACCV '95 Invited Session Papers from the Second Asian Conference on Computer Vision: Recent Developments in Computer Vision
Approximate String-Matching over Suffix Trees
CPM '93 Proceedings of the 4th Annual Symposium on Combinatorial Pattern Matching
A (Sub)Graph Isomorphism Algorithm for Matching Large Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph indexing based on discriminative frequent structure analysis
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2004
Closure-Tree: An Index Structure for Graph Queries
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Fg-index: towards verification-free query processing on graph databases
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
A novel spectral coding in a large graph database
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
EGDIM: evolving graph database indexing method
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
Querying subgraph sets with g-tries
DBSocial '12 Proceedings of the 2nd ACM SIGMOD Workshop on Databases and Social Networks
Compressed feature-based filtering and verification approach for subgraph search
Proceedings of the 16th International Conference on Extending Database Technology
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Biomedical and chemical databases are large and rapidly growing in size. Graphs naturally model such kinds of data. To fully exploit the wealth of information in these graph databases, scientists require systems that search for all occurrences of a query graph. To deal efficiently with graph searching, advanced methods for indexing, representation and matching of graphs have been proposed. This paper presents GraphGrepSX. The system implements efficient graph searching algorithms together with an advanced filtering technique. GraphGrepSX is compared with SING, GraphFind, CTree and GCoding. Experiments show that GraphGrepSX outperforms the compared systems on a very large collection of molecular data. In particular, it reduces the size and the time for the construction of large database index and outperforms the most popular systems.