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PPOPP
2005
ACM
16 years 5 days ago
A sampling-based framework for parallel data mining
The goal of data mining algorithm is to discover useful information embedded in large databases. Frequent itemset mining and sequential pattern mining are two important data minin...
Shengnan Cong, Jiawei Han, Jay Hoeflinger, David A...
VLDB
1991
ACM
143views Database» more  VLDB 1991»
15 years 10 months ago
Handling Data Skew in Multiprocessor Database Computers Using Partition Tuning
Shared nothing multiprocessor archit.ecture is known t.obe more scalable to support very large databases. Compared to other join strategies, a hash-ba9ed join algorithm is particu...
Kien A. Hua, Chiang Lee
PODC
2010
ACM
15 years 8 months ago
Distributed data classification in sensor networks
Low overhead analysis of large distributed data sets is necessary for current data centers and for future sensor networks. In such systems, each node holds some data value, e.g., ...
Ittay Eyal, Idit Keidar, Raphael Rom
CIKM
1997
Springer
15 years 10 months ago
Learning Belief Networks from Data: An Information Theory Based Approach
This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
Jie Cheng, David A. Bell, Weiru Liu
191
Voted
KES
2008
Springer
15 years 5 months ago
Fast Cryptographic Privacy Preserving Association Rules Mining on Distributed Homogenous Data Base
Privacy is one of the most important properties of an information system must satisfy. In which systems the need to share information among different, not trusted entities, the pro...
Mahmoud Hussein, Ashraf El-Sisi, Nabil A. Ismail