A New Algorithm for Error-Tolerant Subgraph Isomorphism Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Matching and Indexing of Graph Models in Content-Based Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
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Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Similarity Searching in Medical Image Databases
IEEE Transactions on Knowledge and Data Engineering
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
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
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
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
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Proceedings of the 2008 ACM SIGMOD international conference on Management of data
PEGASUS: A Peta-Scale Graph Mining System Implementation and Observations
ICDM '09 Proceedings of the 2009 Ninth IEEE International Conference on Data Mining
HadoopDB: an architectural hybrid of MapReduce and DBMS technologies for analytical workloads
Proceedings of the VLDB Endowment
Managing and Mining Graph Data
Managing and Mining Graph Data
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This paper proposes an efficient approach to subgraph search over a large graph database under the MapReduce framework. The main idea is first to build inverted edge indexes for graphs in the database, and then to retrieve data only related to the query subgraph by using the built indexes to answer the query. Experimental results show that the proposed approach has good performance and scalability.