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» Learning from Highly Structured Data by Decomposition
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SAC
2005
ACM
15 years 10 months ago
Rearranging data objects for efficient and stable clustering
When a partitional structure is derived from a data set using a data mining algorithm, it is not unusual to have a different set of outcomes when it runs with a different order of...
Gyesung Lee, Xindong Wu, Jinho Chon
ICANN
2009
Springer
15 years 9 months ago
Constrained Learning Vector Quantization or Relaxed k-Separability
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
Marek Grochowski, Wlodzislaw Duch
SDM
2009
SIAM
180views Data Mining» more  SDM 2009»
16 years 1 months ago
Structure and Dynamics of Research Collaboration in Computer Science.
Complex systems exhibit emergent patterns of behavior at different levels of organization. Powerful network analysis methods, developed in physics and social sciences, have been s...
Andre Nash, Christian Bird, Earl T. Barr, Premkuma...
242
Voted
ICDE
2006
IEEE
146views Database» more  ICDE 2006»
16 years 6 months ago
Query Selection Techniques for Efficient Crawling of Structured Web Sources
The high quality, structured data from Web structured sources is invaluable for many applications. Hidden Web databases are not directly crawlable by Web search engines and are on...
Ping Wu, Ji-Rong Wen, Huan Liu, Wei-Ying Ma
VISUALIZATION
2005
IEEE
15 years 10 months ago
Opening the Black Box - Data Driven Visualization of Neural Network
Arti cial neural networks are computer software or hardware models inspired by the structure and behavior of neurons in the human nervous system. As a powerful learning tool, incr...
Fan-Yin Tzeng, Kwan-Liu Ma