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» Clustering Improves the Exploration of Graph Mining Results
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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
SDM
2009
SIAM
223views Data Mining» more  SDM 2009»
14 years 1 months ago
Context Aware Trace Clustering: Towards Improving Process Mining Results.
Process Mining refers to the extraction of process models from event logs. Real-life processes tend to be less structured and more flexible. Traditional process mining algorithms...
R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aa...
PAKDD
2007
ACM
184views Data Mining» more  PAKDD 2007»
13 years 10 months ago
Exploring Group Moving Pattern for an Energy-Constrained Object Tracking Sensor Network
In this paper, we investigate and utilize the characteristic of the group movement of objects to achieve energy conservation in the inherently resource-constrained wireless object ...
Hsiao-Ping Tsai, De-Nian Yang, Wen-Chih Peng, Ming...
KDD
2009
ACM
182views Data Mining» more  KDD 2009»
14 years 5 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
KDD
2004
ACM
136views Data Mining» more  KDD 2004»
14 years 5 months ago
Exploring the community structure of newsgroups
d Abstract] Christian Borgs Jennifer Chayes Mohammad Mahdian Amin Saberi We propose to use the community structure of Usenet for organizing and retrieving the information stored i...
Christian Borgs, Jennifer T. Chayes, Mohammad Mahd...