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» Clustering Improves the Exploration of Graph Mining Results
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KDD
2009
ACM
204views Data Mining» more  KDD 2009»
16 years 9 days ago
DOULION: counting triangles in massive graphs with a coin
Counting the number of triangles in a graph is a beautiful algorithmic problem which has gained importance over the last years due to its significant role in complex network analy...
Charalampos E. Tsourakakis, U. Kang, Gary L. Mille...
PKDD
2007
Springer
132views Data Mining» more  PKDD 2007»
15 years 5 months ago
An Algorithm to Find Overlapping Community Structure in Networks
Recent years have seen the development of many graph clustering algorithms, which can identify community structure in networks. The vast majority of these only find disjoint commun...
Steve Gregory
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 5 days ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
AI
2005
Springer
15 years 1 months ago
Integrating Web Content Clustering into Web Log Association Rule Mining
Abstract. One of the effects of the general Internet growth is an immense number of user accesses to WWW resources. These accesses are recorded in the web server log files, which...
Jiayun Guo, Vlado Keselj, Qigang Gao
UAI
2004
15 years 1 months ago
Graph Partition Strategies for Generalized Mean Field Inference
An autonomous variational inference algorithm for arbitrary graphical models requires the ability to optimize variational approximations over the space of model parameters as well...
Eric P. Xing, Michael I. Jordan