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SADM
2010
123views more  SADM 2010»
13 years 2 months ago
Discriminative frequent subgraph mining with optimality guarantees
The goal of frequent subgraph mining is to detect subgraphs that frequently occur in a dataset of graphs. In classification settings, one is often interested in discovering discr...
Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei H...
CIKM
2010
Springer
13 years 3 months ago
Mining interesting link formation rules in social networks
Link structures are important patterns one looks out for when modeling and analyzing social networks. In this paper, we propose the task of mining interesting Link Formation rules...
Cane Wing-ki Leung, Ee-Peng Lim, David Lo, Jianshu...
IFIP12
2007
13 years 6 months ago
Clustering Improves the Exploration of Graph Mining Results
Mining frequent subgraphs is an area of research where we have a given set of graphs, and where we search for (connected) subgraphs contained in many of these graphs. Each graph ca...
Edgar H. de Graaf, Joost N. Kok, Walter A. Kosters
CIDM
2009
IEEE
13 years 8 months ago
Empirical comparison of graph classification algorithms
The graph classification problem is learning to classify separate, individual graphs in a graph database into two or more categories. A number of algorithms have been introduced fo...
Nikhil S. Ketkar, Lawrence B. Holder, Diane J. Coo...
ICDM
2006
IEEE
184views Data Mining» more  ICDM 2006»
13 years 10 months ago
MARGIN: Maximal Frequent Subgraph Mining
The exponential number of possible subgraphs makes the problem of frequent subgraph mining a challenge. Maximal frequent mining has triggered much interest since the size of the s...
Lini T. Thomas, Satyanarayana R. Valluri, Kamalaka...
MLG
2007
Springer
13 years 10 months ago
Improving Frequent Subgraph Mining in the Presence of Symmetry
While recent algorithms for mining the frequent subgraphs of a database are efficient in the general case, these algorithms tend to do poorly on databases that have a few or no la...
Christian Desrosiers, Philippe Galinier, Pierre Ha...
EDBT
2009
ACM
138views Database» more  EDBT 2009»
13 years 11 months ago
FOGGER: an algorithm for graph generator discovery
To our best knowledge, all existing graph pattern mining algorithms can only mine either closed, maximal or the complete set of frequent subgraphs instead of graph generators whic...
Zhiping Zeng, Jianyong Wang, Jun Zhang, Lizhu Zhou
SDM
2009
SIAM
149views Data Mining» more  SDM 2009»
14 years 1 months ago
Near-optimal Supervised Feature Selection among Frequent Subgraphs.
Graph classification is an increasingly important step in numerous application domains, such as function prediction of molecules and proteins, computerised scene analysis, and an...
Alexander J. Smola, Arthur Gretton, Hans-Peter Kri...
KDD
2006
ACM
208views Data Mining» more  KDD 2006»
14 years 5 months ago
Frequent subgraph mining in outerplanar graphs
In recent years there has been an increased interest in frequent pattern discovery in large databases of graph structured objects. While the frequent connected subgraph mining pro...
Tamás Horváth, Jan Ramon, Stefan Wro...
ICDE
2009
IEEE
290views Database» more  ICDE 2009»
14 years 6 months ago
GraphSig: A Scalable Approach to Mining Significant Subgraphs in Large Graph Databases
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 graph datab...
Sayan Ranu, Ambuj K. Singh