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» Scalable Parallel Data Mining for Association Rules
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AI
2003
Springer
15 years 5 months ago
Efficient Mining of Indirect Associations Using HI-Mine
Discovering association rules is one of the important tasks in data mining. While most of the existing algorithms are developed for efficient mining of frequent patterns, it has be...
Qian Wan, Aijun An
KDD
1997
ACM
135views Data Mining» more  KDD 1997»
15 years 4 months ago
Brute-Force Mining of High-Confidence Classification Rules
This paper investigates a brute-force technique for mining classification rules from large data sets. We employ an association rule miner enhanced with new pruning strategies to c...
Roberto J. Bayardo Jr.
SAC
2011
ACM
14 years 2 months ago
RuleGrowth: mining sequential rules common to several sequences by pattern-growth
Mining sequential rules from large databases is an important topic in data mining fields with wide applications. Most of the relevant studies focused on finding sequential rules a...
Philippe Fournier-Viger, Roger Nkambou, Vincent Sh...
DATAMINE
1999
140views more  DATAMINE 1999»
14 years 11 months ago
A Scalable Parallel Algorithm for Self-Organizing Maps with Applications to Sparse Data Mining Problems
Abstract. We describe a scalable parallel implementation of the self organizing map (SOM) suitable for datamining applications involving clustering or segmentation against large da...
Richard D. Lawrence, George S. Almasi, Holly E. Ru...
IPPS
2000
IEEE
15 years 4 months ago
Scalable Parallel Clustering for Data Mining on Multicomputers
This paper describes the design and implementation on MIMD parallel machines of P-AutoClass, a parallel version of the AutoClass system based upon the Bayesian method for determini...
D. Foti, D. Lipari, Clara Pizzuti, Domenico Talia