Efficient management of transitive relationships in large data and knowledge bases
SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
On a relation between graph edit distance and maximum common subgraph
Pattern Recognition Letters
Information Retrieval with Conceptual Graph Matching
DEXA '00 Proceedings of the 11th International Conference on Database and Expert Systems Applications
STOC '83 Proceedings of the fifteenth annual ACM symposium on Theory of computing
Frequent Substructure-Based Approaches for Classifying Chemical Compounds
IEEE Transactions on Knowledge and Data Engineering
Dual Labeling: Answering Graph Reachability Queries in Constant Time
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Reverse kNN search in arbitrary dimensionality
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Mining significant graph patterns by leap search
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Partial least squares regression for graph mining
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
GraphSig: A Scalable Approach to Mining Significant Subgraphs in Large Graph Databases
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Graph classification based on pattern co-occurrence
Proceedings of the 18th ACM conference on Information and knowledge management
Comparing stars: on approximating graph edit distance
Proceedings of the VLDB Endowment
GAIA: graph classification using evolutionary computation
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Semi-supervised feature selection for graph classification
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Fast computation of reachability labeling for large graphs
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Graph classification: a diversified discriminative feature selection approach
Proceedings of the 21st ACM international conference on Information and knowledge management
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Graph classification has become an increasingly important research topic in recent years due to its wide applications. However, one interesting problem about how to classify graphs based on the implicit properties of graphs has not been studied yet. To address it, this paper first conducts an extensive study on existing graph theoretical metrics and also propose various novel metrics to discover implicit graph properties. We then apply feature selection techniques to discover a subset of discriminative metrics by considering domain knowledge. Two classifiers are proposed to classify the graphs based on the subset of features. The feasibility of graph classification based on the proposed graph metrics and techniques has been experimentally studied.