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AUSAI
2003
Springer
15 years 2 months ago
Efficiently Mining Frequent Patterns from Dense Datasets Using a Cluster of Computers
Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we pr...
Yudho Giri Sucahyo, Raj P. Gopalan, Amit Rudra
ICDM
2010
IEEE
264views Data Mining» more  ICDM 2010»
14 years 7 months ago
Block-GP: Scalable Gaussian Process Regression for Multimodal Data
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
Kamalika Das, Ashok N. Srivastava
ICDE
2007
IEEE
131views Database» more  ICDE 2007»
15 years 4 months ago
Incremental Clustering of Mobile Objects
Moving objects are becoming increasingly attractive to the data mining community due to continuous advances in technologies like GPS, mobile computers, and wireless communication ...
Sigal Elnekave, Mark Last, Oded Maimon
SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
15 years 2 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
KDD
2002
ACM
118views Data Mining» more  KDD 2002»
15 years 10 months ago
SECRET: a scalable linear regression tree algorithm
Recently there has been an increasing interest in developing regression models for large datasets that are both accurate and easy to interpret. Regressors that have these properti...
Alin Dobra, Johannes Gehrke