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IFIP12
2007
15 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
BMCBI
2004
120views more  BMCBI 2004»
15 years 4 months ago
Clustering under the line graph transformation: application to reaction network
Background: Many real networks can be understood as two complementary networks with two kind of nodes. This is the case of metabolic networks where the first network has chemical ...
Jose C. Nacher, Nobuhisa Ueda, Takuji Yamada, Mino...
TVCG
2008
145views more  TVCG 2008»
15 years 4 months ago
Geometry-Based Edge Clustering for Graph Visualization
Graphs have been widely used to model relationships among data. For large graphs, excessive edge crossings make the display visually cluttered and thus difficult to explore. In thi...
Weiwei Cui, Hong Zhou, Huamin Qu, Pak Chung Wong, ...
KDD
2007
ACM
168views Data Mining» more  KDD 2007»
16 years 4 months ago
A probabilistic framework for relational clustering
Relational clustering has attracted more and more attention due to its phenomenal impact in various important applications which involve multi-type interrelated data objects, such...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu
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WWW
2008
ACM
16 years 5 months ago
Graph theoretical framework for simultaneously integrating visual and textual features for efficient web image clustering
With the explosive growth of Web and the recent development in digital media technology, the number of images on the Web has grown tremendously. Consequently, Web image clustering...
Manjeet Rege, Ming Dong, Jing Hua