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» Scalable mining of large disk-based graph databases
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EDBT
2008
ACM
160views Database» more  EDBT 2008»
13 years 9 months ago
Taxonomy-superimposed graph mining
New graph structures where node labels are members of hierarchically organized ontologies or taxonomies have become commonplace in different domains, e.g., life sciences. It is a ...
Ali Cakmak, Gultekin Özsoyoglu
KDD
2009
ACM
182views Data Mining» more  KDD 2009»
14 years 8 months ago
Scalable graph clustering using stochastic flows: applications to community discovery
Algorithms based on simulating stochastic flows are a simple and natural solution for the problem of clustering graphs, but their widespread use has been hampered by their lack of...
Venu Satuluri, Srinivasan Parthasarathy
PVLDB
2010
200views more  PVLDB 2010»
13 years 5 months ago
SAPPER: Subgraph Indexing and Approximate Matching in Large Graphs
With the emergence of new applications, e.g., computational biology, new software engineering techniques, social networks, etc., more data is in the form of graphs. Locating occur...
Shijie Zhang, Jiong Yang, Wei Jin
KDD
2007
ACM
184views Data Mining» more  KDD 2007»
14 years 8 months ago
GraphScope: parameter-free mining of large time-evolving graphs
How can we find communities in dynamic networks of social interactions, such as who calls whom, who emails whom, or who sells to whom? How can we spot discontinuity timepoints in ...
Jimeng Sun, Christos Faloutsos, Spiros Papadimitri...
ICDM
2007
IEEE
118views Data Mining» more  ICDM 2007»
14 years 1 months ago
Subgraph Support in a Single Large Graph
—Defining the support (or frequency) of a subgraph is trivial when a database of graphs is given: it is simply the number of graphs in the database that contain the subgraph. Ho...
Mathias Fiedler, Christian Borgelt