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ICTAI
2003
IEEE
14 years 25 days ago
Parallel Mining of Maximal Frequent Itemsets from Databases
In this paper, we propose a parallel algorithm for mining maximal frequent itemsets from databases. A frequent itemset is maximal if none of its supersets is frequent. The new par...
Soon Myoung Chung, Congnan Luo
GPEM
2007
119views more  GPEM 2007»
13 years 7 months ago
Genomic mining for complex disease traits with "random chemistry"
Our rapidly growing knowledge regarding genetic variation in the human genome offers great potential for understanding the genetic etiology of disease. This, in turn, could revolut...
Margaret J. Eppstein, Joshua L. Payne, Bill C. Whi...
KDD
2002
ACM
196views Data Mining» more  KDD 2002»
14 years 8 months ago
Comparing Two Recommender Algorithms with the Help of Recommendations by Peers
Abstract. Since more and more Web sites, especially sites of retailers, offer automatic recommendation services using Web usage mining, evaluation of recommender algorithms has bec...
Andreas Geyer-Schulz, Michael Hahsler
ADC
2003
Springer
182views Database» more  ADC 2003»
14 years 24 days 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
ISMIR
2000
Springer
148views Music» more  ISMIR 2000»
13 years 11 months ago
IR for Contemporary Music: What the Musicologist Needs
Active listening is the core of musical activity Listening does not only concern receiving musical information. On the contrary, it is "active" and based on a set of int...
Alain Bonardi