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» Clustering Improves the Exploration of Graph Mining Results
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ICPR
2010
IEEE
14 years 9 months ago
Semi-supervised Graph Learning: Near Strangers or Distant Relatives
In this paper, an easily implemented semi-supervised graph learning method is presented for dimensionality reduction and clustering, using the most of prior knowledge from limited...
Weifu Chen, Guocan Feng
KDD
2002
ACM
182views Data Mining» more  KDD 2002»
16 years 7 days ago
On the need for time series data mining benchmarks: a survey and empirical demonstration
In the last decade there has been an explosion of interest in mining time series data. Literally hundreds of papers have introduced new algorithms to index, classify, cluster and s...
Eamonn J. Keogh, Shruti Kasetty
CGF
2010
189views more  CGF 2010»
14 years 12 months ago
Space-in-Time and Time-in-Space Self-Organizing Maps for Exploring Spatiotemporal Patterns
Spatiotemporal data pose serious challenges to analysts in geographic and other domains. Owing to the complexity of the geospatial and temporal components, this kind of data canno...
Gennady L. Andrienko, Natalia V. Andrienko, Sebast...
ICDM
2006
IEEE
138views Data Mining» more  ICDM 2006»
15 years 5 months ago
Belief Propagation in Large, Highly Connected Graphs for 3D Part-Based Object Recognition
We describe a part-based object-recognition framework, specialized to mining complex 3D objects from detailed 3D images. Objects are modeled as a collection of parts together with...
Frank DiMaio, Jude W. Shavlik
TVCG
2008
121views more  TVCG 2008»
14 years 11 months ago
On the Visualization of Social and other Scale-Free Networks
This paper proposes novel methods for visualizing specifically the large power-law graphs that arise in sociology and the sciences. In such cases a large portion of edges can be sh...
Yuntao Jia, Jared Hoberock, Michael Garland, John ...