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» Clustering Improves the Exploration of Graph Mining Results
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AFRIGRAPH
2004
ACM
15 years 5 months ago
Visualizing 3D scenes using non-linear projections and data mining of previous camera movements
We describe techniques for exploring 3D scenes by combining non-linear projections with the interactive data mining of camera navigations from previous explorations. Our approach ...
Karan Singh, Ravin Balakrishnan
SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
15 years 1 months ago
Simultaneous Unsupervised Learning of Disparate Clusterings
Most clustering algorithms produce a single clustering for a given data set even when the data can be clustered naturally in multiple ways. In this paper, we address the difficult...
Prateek Jain, Raghu Meka, Inderjit S. Dhillon
ICASSP
2010
IEEE
15 years 23 hour ago
Towards multi-speaker unsupervised speech pattern discovery
In this paper, we explore the use of a Gaussian posteriorgram based representation for unsupervised discovery of speech patterns. Compared with our previous work, the new approach...
Yaodong Zhang, James R. Glass
KDD
1998
ACM
164views Data Mining» more  KDD 1998»
15 years 4 months ago
A Data Mining Support Environment and its Application on Insurance Data
Huge masses of digital data about products, customers and competitors have become available for companies in the services sector. In order to exploit its inherent (and often hidde...
Martin Staudt, Jörg-Uwe Kietz, Ulrich Reimer
PKDD
2009
Springer
120views Data Mining» more  PKDD 2009»
15 years 6 months ago
Variational Graph Embedding for Globally and Locally Consistent Feature Extraction
Existing feature extraction methods explore either global statistical or local geometric information underlying the data. In this paper, we propose a general framework to learn fea...
Shuang-Hong Yang, Hongyuan Zha, Shaohua Kevin Zhou...