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GRC
2010
IEEE
15 years 8 months ago
Local Pattern Mining from Sequences Using Rough Set Theory
Abstract--Sequential pattern mining is a crucial but challenging task in many applications, e.g., analyzing the behaviors of data in transactions and discovering frequent patterns ...
Ken Kaneiwa, Yasuo Kudo
KDD
2006
ACM
143views Data Mining» more  KDD 2006»
16 years 7 months ago
Mining for misconfigured machines in grid systems
Grid systems are proving increasingly useful for managing the batch computing jobs of organizations. One well known example for that is Intel which uses an internally developed sy...
Noam Palatin, Arie Leizarowitz, Assaf Schuster, Ra...
KDD
2010
ACM
247views Data Mining» more  KDD 2010»
15 years 9 months ago
Metric forensics: a multi-level approach for mining volatile graphs
Advances in data collection and storage capacity have made it increasingly possible to collect highly volatile graph data for analysis. Existing graph analysis techniques are not ...
Keith Henderson, Tina Eliassi-Rad, Christos Falout...
ICDM
2003
IEEE
115views Data Mining» more  ICDM 2003»
16 years 5 days ago
Icon-based Visualization of Large High-Dimensional Datasets
High dimensional data visualization is critical to data analysts since it gives a direct view of original data. We present a method to visualize large amount of high dimensional d...
Ping Chen, Chenyi Hu, Wei Ding 0003, Heloise Lynn,...
KDD
2001
ACM
216views Data Mining» more  KDD 2001»
16 years 7 months ago
Real world performance of association rule algorithms
This study compares five well-known association rule algorithms using three real-world datasets and an artificial dataset. The experimental results confirm the performance improve...
Zijian Zheng, Ron Kohavi, Llew Mason