GraphLog: a visual formalism for real life recursion
PODS '90 Proceedings of the ninth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
An Algorithm for Subgraph Isomorphism
Journal of the ACM (JACM)
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Efficient Mining of Frequent Subgraphs in the Presence of Isomorphism
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Graph indexing: a frequent structure-based approach
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Substructure similarity search in graph databases
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
A Toolkit for Addressing HCI Issues in Visual Language Environments
VLHCC '05 Proceedings of the 2005 IEEE Symposium on Visual Languages and Human-Centric Computing
Closure-Tree: An Index Structure for Graph Queries
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
A query language for biological networks
Bioinformatics
Making database systems usable
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Fast and practical indexing and querying of very large graphs
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Fg-index: towards verification-free query processing on graph databases
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
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
Graphs-at-a-time: query language and access methods for graph databases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Taming verification hardness: an efficient algorithm for testing subgraph isomorphism
Proceedings of the VLDB Endowment
GBLENDER: visual subgraph query formulation meets query processing
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
QUBLE: blending visual subgraph query formulation with query processing on large networks
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
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Given a graph database D and a query graph g, an exact subgraph matching query asks for the set S of graphs in D that contain g as a subgraph. This type of queries find important applications in several domains such as bioinformatics and chemoinformatics, where users are generally not familiar with complex graph query languages. Consequently, user-friendly visual interfaces which support query graph construction can reduce the burden of data retrieval for these users. Existing techniques for subgraph matching queries built on top of such visual framework are designed to optimize the time required in retrieving the result set S from D, assuming that the whole query graph has been constructed. This leads to sub-optimal system response time as the query processing is initiated only after the user has finished drawing the query graph. In this paper, we take the first step towards exploring a novel graph query processing paradigm, where instead of processing a query graph after its construction, it interleaves visual query construction and processing to improve system response time. To realize this, we present an algorithm called GBLENDER that prunes false results and prefetches partial query results by exploiting the latency offered by the visual query formulation. It employs a novel action-aware indexing scheme that exploits users' interaction characteristics with visual interfaces to support efficient retrieval. Extensive experiments on both real and synthetic datasets demonstrate the effectiveness and efficiency of our solution.