Frequent pattern mining: current status and future directions
J Han, H Cheng, D ** frequent subgraph mining for bioinformatics applications
Searching for interesting common subgraphs in graph data is a well-studied problem in data
mining. Subgraph mining techniques focus on the discovery of patterns in graphs that exhibit …
mining. Subgraph mining techniques focus on the discovery of patterns in graphs that exhibit …
Spin: mining maximal frequent subgraphs from graph databases
One fundamental challenge for mining recurring subgraphs from semi-structured data sets is
the overwhelming abundance of such patterns. In large graph databases, the total number of …
the overwhelming abundance of such patterns. In large graph databases, the total number of …
Graph database indexing using structured graph decomposition
We introduce a novel method of indexing graph databases in order to facilitate subgraph
isomorphism and similarity queries. The index is comprised of two major data structures. The …
isomorphism and similarity queries. The index is comprised of two major data structures. The …
[BOOK][B] Handbook of computational molecular biology
S Aluru - 2005 - taylorfrancis.com
The enormous complexity of biological systems at the molecular level must be answered
with powerful computational methods. Computational biology is a young field, but has seen …
with powerful computational methods. Computational biology is a young field, but has seen …
Summarizing itemset patterns: a profile-based approach
Frequent-pattern mining has been studied extensively on scalable methods for mining
various kinds of patterns including itemsets, sequences, and graphs. However, the …
various kinds of patterns including itemsets, sequences, and graphs. However, the …
Mining closed relational graphs with connectivity constraints
Relational graphs are widely used in modeling large scale networks such as biological
networks and social networks. In this kind of graph, connectivity becomes critical in …
networks and social networks. In this kind of graph, connectivity becomes critical in …
Output space sampling for graph patterns
Recent interest in graph pattern mining has shifted from finding all frequent subgraphs to
obtaining a small subset of frequent subgraphs that are representative, discriminative or …
obtaining a small subset of frequent subgraphs that are representative, discriminative or …
Mining behavior graphs for “backtrace” of noncrashing bugs
Analyzing the executions of a buggy software program is essentially a data mining process.
Although many interesting methods have been developed to trace crashing bugs (such as …
Although many interesting methods have been developed to trace crashing bugs (such as …