Principles of artificial intelligence
Principles of artificial intelligence
An Algorithm for Subgraph Isomorphism
Journal of the ACM (JACM)
Algorithmics and applications of tree and graph searching
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
IEEE Intelligent Systems
Graph-based technologies for intelligence analysis
Communications of the ACM - Homeland security
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Finding Frequent Patterns in a Large Sparse Graph*
Data Mining and Knowledge Discovery
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Fast best-effort pattern matching in large attributed graphs
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Measurement and analysis of online social networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Graph Twiddling in a MapReduce World
Computing in Science and Engineering
APPT '09 Proceedings of the 8th International Symposium on Advanced Parallel Processing Technologies
Substructure discovery using minimum description length and background knowledge
Journal of Artificial Intelligence Research
DOGMA: A Disk-Oriented Graph Matching Algorithm for RDF Databases
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Kronecker Graphs: An Approach to Modeling Networks
The Journal of Machine Learning Research
COSI: Cloud Oriented Subgraph Identification in Massive Social Networks
ASONAM '10 Proceedings of the 2010 International Conference on Advances in Social Networks Analysis and Mining
Hadoop: The Definitive Guide
Realistic, mathematically tractable graph generation and evolution, using kronecker multiplication
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
An In-depth Study of Stochastic Kronecker Graphs
ICDM '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining
MapReduce in MPI for Large-scale graph algorithms
Parallel Computing
Inexact graph matching for structural pattern recognition
Pattern Recognition Letters
SAHAD: Subgraph Analysis in Massive Networks Using Hadoop
IPDPS '12 Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium
A space efficient streaming algorithm for triangle counting using the birthday paradox
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
| Hi-index | 0.00 |
Inexact subgraph matching based on type-isomorphism was introduced by Berry et al. [J. Berry, B. Hendrickson, S. Kahan, P. Konecny, Software and algorithms for graph queries on multithreaded architectures, in: Proc. IEEE International Parallel and Distributed Computing Symposium, IEEE, 2007, pp. 1-14] as a generalization of the exact subgraph matching problem. Enumerating small subgraph patterns in very large graphs is a core problem in the analysis of social networks, bioinformatics data sets, and other applications. This paper describes a MapReduce algorithm for subgraph type-isomorphism matching. The MapReduce computing framework is designed for distributed computing on massive data sets, and the new algorithm leverages MapReduce techniques to enable processing of graphs with billions of vertices. The paper also introduces a new class of walk-level constraints for narrowing the set of matches. Constraints meeting criteria defined in the paper are useful for specifying more precise patterns and for improving algorithm performance. Results are provided on a variety of graphs, with size ranging up to billions of vertices and edges, including graphs that follow a power law degree distribution.