Fast discovery of association rules
Advances in knowledge discovery and data mining
Efficiently mining long patterns from databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
A probabilistic framework for semi-supervised clustering
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
SPIN: mining maximal frequent subgraphs from graph databases
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient Algorithms for Mining Closed Itemsets and Their Lattice Structure
IEEE Transactions on Knowledge and Data Engineering
A spectral clustering approach to optimally combining numericalvectors with a modular network
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Finding collections of k-clique percolated components in attributed graphs
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
An FPGA-Based Accelerator for Frequent Itemset Mining
ACM Transactions on Reconfigurable Technology and Systems (TRETS)
Preserving privacy and frequent sharing patterns for social network data publishing
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Weighted path as a condensed pattern in a single attributed DAG
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Itemset mining and graph mining have attracted considerable attention in the field of data mining, since they have many important applications in various areas such as biology, marketing, and social network analysis However, most existing studies focus only on either itemset mining or graph mining, and only a few studies have addressed a combination of both In this paper, we introduce a new problem which we call itemset-sharing subgraph (ISS) set enumeration, where the task is to find sets of subgraphs with common itemsets in a large graph in which each vertex has an associated itemset The problem has various interesting potential applications such as in side-effect analysis in drug discovery and the analysis of the influence of word-of-mouth communication in marketing in social networks We propose an efficient algorithm ROBIN for finding ISS sets in such graph; this algorithm enumerates connected subgraphs having common itemsets and finds their combinations Experiments using a synthetic network verify that our method can efficiently process networks with more than one million edges Experiments using a real biological network show that our algorithm can find biologically interesting patterns We also apply ROBIN to a citation network and find successful collaborative research works.