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A survey on subgraph counting: concepts, algorithms, and applications to network motifs and graphlets
Computing subgraph frequencies is a fundamental task that lies at the core of several
network analysis methodologies, such as network motifs and graphlet-based metrics, which …
network analysis methodologies, such as network motifs and graphlet-based metrics, which …
A primer to frequent itemset mining for bioinformatics
Over the past two decades, pattern mining techniques have become an integral part of many
bioinformatics solutions. Frequent itemset mining is a popular group of pattern mining …
bioinformatics solutions. Frequent itemset mining is a popular group of pattern mining …
Graph-based substructure pattern mining with edge-weight
To represent complex inter-relationships among entities, weighted graphs are more useful
than their unweighted counterparts. In a transactional graph setting, researchers have made …
than their unweighted counterparts. In a transactional graph setting, researchers have made …
Graphsig: A scalable approach to mining significant subgraphs in large graph databases
S Ranu, AK Singh - 2009 IEEE 25th International Conference …, 2009 - ieeexplore.ieee.org
Graphs are being increasingly used to model a wide range of scientific data. Such
widespread usage of graphs has generated considerable interest in mining patterns from …
widespread usage of graphs has generated considerable interest in mining patterns from …
Margin: Maximal frequent subgraph mining
The exponential number of possible subgraphs makes the problem of frequent subgraph
mining a challenge. The set of maximal frequent subgraphs is much smaller to that of the set …
mining a challenge. The set of maximal frequent subgraphs is much smaller to that of the set …
The atlas for the aspiring network scientist
M Coscia - ar** temporal trends from a multivariate panel of physiologic measurements
Y Luo, Y ** 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 …
T-FSM: A task-based system for massively parallel frequent subgraph pattern mining from a big graph
Finding frequent subgraph patterns in a big graph is an important problem with many
applications such as classifying chemical compounds and building indexes to speed up …
applications such as classifying chemical compounds and building indexes to speed up …