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IPPS
1999
IEEE
13 years 11 months ago
Parallel Out-of-Core Divide-and-Conquer Techniques with Application to Classification Trees
Classification is an important problem in the field of data mining. Construction of good classifiers is computationally intensive and offers plenty of scope for parallelization. D...
Mahesh K. Sreenivas, Khaled Alsabti, Sanjay Ranka
ICDE
2002
IEEE
104views Database» more  ICDE 2002»
14 years 8 months ago
Efficient Evaluation of Queries with Mining Predicates
Modern relational database systems are beginning to support ad hoc queries on mining models. In this paper, we explore novel techniques for optimizing queries that apply mining mo...
Surajit Chaudhuri, Vivek R. Narasayya, Sunita Sara...
PPOPP
2005
ACM
14 years 1 months 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...
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COR
2004
115views more  COR 2004»
13 years 7 months ago
Evaluation of decision trees: a multi-criteria approach
Data mining (DM) techniques are being increasingly used in many modern organizations to retrieve valuable knowledge structures from organizational databases, including data wareho...
Kweku-Muata Osei-Bryson
DEXAW
1998
IEEE
116views Database» more  DEXAW 1998»
13 years 11 months ago
Data-Mining: A Tightly-Coupled Implementation on a Parallel Database Server
Due to the increasingly di culty of discovering patterns in real-world databases using only conventional OLAP tools, an automated process such as data mining is currently essentia...
Mauro Sousa, Marta Mattoso, Nelson F. F. Ebecken