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ADC
2003
Springer
182views Database» more  ADC 2003»
15 years 11 months ago
CT-ITL : Efficient Frequent Item Set Mining Using a Compressed Prefix Tree with Pattern Growth
Discovering association rules that identify relationships among sets of items is an important problem in data mining. Finding frequent item sets is computationally the most expens...
Yudho Giri Sucahyo, Raj P. Gopalan
SIGMOD
1999
ACM
112views Database» more  SIGMOD 1999»
15 years 10 months ago
A New Method for Similarity Indexing of Market Basket Data
In recent years, many data mining methods have been proposed for finding useful and structured information from market basket data. The association rule model was recently propos...
Charu C. Aggarwal, Joel L. Wolf, Philip S. Yu
KDD
2005
ACM
89views Data Mining» more  KDD 2005»
16 years 6 months ago
Mining risk patterns in medical data
In this paper, we discuss a problem of finding risk patterns in medical data. We define risk patterns by a statistical metric, relative risk, which has been widely used in epidemi...
Jiuyong Li, Ada Wai-Chee Fu, Hongxing He, Jie Chen...
KDD
2003
ACM
113views Data Mining» more  KDD 2003»
16 years 6 months ago
Mining unexpected rules by pushing user dynamics
Unexpected rules are interesting because they are either previously unknown or deviate from what prior user knowledge would suggest. In this paper, we study three important issues...
Ke Wang, Yuelong Jiang, Laks V. S. Lakshmanan
ICCS
2003
Springer
15 years 11 months ago
A Compress-Based Association Mining Algorithm for Large Dataset
The association mining is one of the primary sub-areas in the field of data mining. This technique had been used in numerous practical applications, including consumer market baske...
Mafruz Zaman Ashrafi, David Taniar, Kate A. Smith