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graph mining
Description:
Graph mining is the computational analysis of graph-structured data to discover patterns, relationships, and useful knowledge.
Primary topic:
Graph Theory and Algorithms (33%)
Related topics:
Graph Theory and Algorithms (33%),
Data Mining Algorithms and Applications (15%),
Complex Network Analysis Techniques (9%)
OpenAlex ID:
keywords/graph-mining
gSpan: graph-based substructure pattern mining
2003
·
Xifeng Yan
, Jiawei Han
·
Proceedings
·
2,062
Frequent subgraph discovery
2002
·
M. Kuramochi
, G. Karypis
·
Proceedings
·
1,083
Encyclopedia of Machine Learning and Data Mining
2017
·
Webb, Geoffrey I
, Sammut, Claude
·
Springer eBooks
·
914
Shortest-Path Kernels on Graphs
2006
·
K.M. Borgwardt
, H. Kriegel
·
Proceedings
·
887
GraphChi: Large-Scale Graph Computation on Just a PC
2018
·
Kyrola, Aapo
, Blelloch, Guy E.
, et al.
·
Figshare
·
868
PDF
CloseGraph
2003
·
Xifeng Yan
, Jiawei Han
·
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)
·
635
PEGASUS: A Peta-Scale Graph Mining System Implementation and Observations
2009
·
U. Kang
, Charalampos E. Tsourakakis
, et al.
·
Proceedings
·
630
Graph mining
2006
·
Deepayan Chakrabarti
, Christos Faloutsos
·
ACM Computing Surveys
·
611
Managing and Mining Graph Data
2010
·
Charu C. Aggarwal
, Haixun Wang
·
The Kluwer international series on advances in database systems
·
599
The community-search problem and how to plan a successful cocktail party
2010
·
Mauro Sozio
, Aristides Gionis
·
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)
·
499
A quickstart in frequent structure mining can make a difference
2004
·
Siegfried Nijssen
, Joost N. Kok
·
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)
·
474
Data Mining: The Textbook
2015
·
Charų C. Aggarwal
·
473
State of the art of graph-based data mining
2003
·
Takashi Washio
, Hiroshi Motoda
·
ACM SIGKDD Explorations Newsletter
·
448
Graph-based data mining
2000
·
D.J. Cook
, L.B. Holder
·
IEEE Intelligent Systems and their Applications
·
406
Mining Graph Data
2006
·
Diane J. Cook
, Lawrence B. Holder
·
Wiley-Interscience eBooks
·
393
Frequent substructure-based approaches for classifying chemical compounds
2005
·
M. Deshpande
, M. Kuramochi
, et al.
·
IEEE Transactions on Knowledge and Data Engineering
·
371
An efficient algorithm for discovering frequent subgraphs
2004
·
M. Kuramochi
, G. Karypis
·
IEEE Transactions on Knowledge and Data Engineering
·
352
A survey of frequent subgraph mining algorithms
2012
·
Chuntao Jiang
, Frans Coenen
, et al.
·
The Knowledge Engineering Review
·
346
DOULION
2009
·
Charalampos E. Tsourakakis
, U. Kang
, et al.
·
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)
·
328
Clique Relaxations in Social Network Analysis: The Maximum k -Plex Problem
2011
·
Balabhaskar Balasundaram
, Sergiy Butenko
, et al.
·
Operations Research
·
302
Denser than the densest subgraph
2013
·
Charalampos Tsourakakis
, Francesco Bonchi
, et al.
·
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)
·
294
False Information on Web and Social Media: A Survey
2018
·
Kumar, Srijan
, Shah, Neil
·
arXiv (Cornell University)
·
289
PDF
Complete Mining of Frequent Patterns from Graphs: Mining Graph Data
2003
·
Akihiro Inokuchi
, Takashi Washio
, et al.
·
Machine Learning
·
279
PDF
Acing the IOC Game
2016
·
Xiaojing Liao
, Kan Yuan
, et al.
·
ACM SIGSAC Conference on Computer and Communications Security (CCS)
·
276
PDF
ANF
2002
·
Christopher R. Palmer
, Phillip B. Gibbons
, et al.
·
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)
·
266
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Works count:
3,577
Citation count:
47,950
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