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KDD
2003
ACM
195views Data Mining» more  KDD 2003»
16 years 5 months ago
Visualizing changes in the structure of data for exploratory feature selection
Using visualization techniques to explore and understand high-dimensional data is an efficient way to combine human intelligence with the immense brute force computation power ava...
Elias Pampalk, Werner Goebl, Gerhard Widmer
123
Voted
KDD
2005
ACM
107views Data Mining» more  KDD 2005»
15 years 10 months ago
Cross-relational clustering with user's guidance
Clustering is an essential data mining task with numerous applications. However, data in most real-life applications are high-dimensional in nature, and the related information of...
Xiaoxin Yin, Jiawei Han, Philip S. Yu
163
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WISE
2002
Springer
15 years 10 months ago
A Unified Framework for Clustering Heterogeneous Web Objects
In this paper, we introduce a novel framework for clustering web data which is often heterogeneous in nature. As most existing methods often integrate heterogeneous data into a un...
Hua-Jun Zeng, Zheng Chen, Wei-Ying Ma
PRIS
2004
15 years 6 months ago
Comparison of Combination Methods using Spectral Clustering Ensembles
We address the problem of the combination of multiple data partitions, that we call a clustering ensemble. We use a recent clustering approach, known as Spectral Clustering, and th...
André Lourenço, Ana L. N. Fred
121
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DATAMINE
2007
110views more  DATAMINE 2007»
15 years 5 months ago
The complexity of non-hierarchical clustering with instance and cluster level constraints
Recent work has looked at extending clustering algorithms with instance level must-link (ML) and cannot-link (CL) background information. Our work introduces δ and ǫ cluster lev...
Ian Davidson, S. S. Ravi