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» Generating Synthetic Data to Match Data Mining Patterns
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ADMA
2009
Springer
186views Data Mining» more  ADMA 2009»
15 years 4 months ago
Mining Compressed Repetitive Gapped Sequential Patterns Efficiently
Mining frequent sequential patterns from sequence databases has been a central research topic in data mining and various efficient mining sequential patterns algorithms have been p...
Yongxin Tong, Zhao Li, Dan Yu, Shilong Ma, Zhiyuan...
PODS
2003
ACM
151views Database» more  PODS 2003»
15 years 10 months ago
Feasible itemset distributions in data mining: theory and application
Computing frequent itemsets and maximally frequent itemsets in a database are classic problems in data mining. The resource requirements of all extant algorithms for both problems...
Ganesh Ramesh, William Maniatty, Mohammed Javeed Z...
DEXA
2003
Springer
115views Database» more  DEXA 2003»
15 years 3 months ago
On Mining Group Patterns of Mobile Users
In this paper, we present a group pattern mining approach to derive the grouping information of mobile device users based on the spatio-temporal distances among them. Group pattern...
Yida Wang, Ee-Peng Lim, San-Yih Hwang
ICDE
2002
IEEE
146views Database» more  ICDE 2002»
15 years 11 months ago
Data Mining Meets Performance Evaluation: Fast Algorithms for Modeling Bursty Traffic
Network, web, and disk I/O traffic are usually bursty, self-similar [9, 3, 5, 6] and therefore can not be modeled adequately with Poisson arrivals[9]. However, we do want to model...
Mengzhi Wang, Ngai Hang Chan, Spiros Papadimitriou...
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ICDM
2005
IEEE
139views Data Mining» more  ICDM 2005»
15 years 3 months ago
Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation
In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data ...
Yongge Wang, Xintao Wu