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» Mining Very Large Databases
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SDM
2008
SIAM
119views Data Mining» more  SDM 2008»
15 years 5 months ago
An Efficient Local Algorithm for Distributed Multivariate Regression in Peer-to-Peer Networks
This paper offers a local distributed algorithm for multivariate regression in large peer-to-peer environments. The algorithm is designed for distributed inferencing, data compact...
Kanishka Bhaduri, Hillol Kargupta
132
Voted
MLDM
2009
Springer
15 years 10 months ago
PMCRI: A Parallel Modular Classification Rule Induction Framework
In a world where massive amounts of data are recorded on a large scale we need data mining technologies to gain knowledge from the data in a reasonable time. The Top Down Induction...
Frederic T. Stahl, Max A. Bramer, Mo Adda
113
Voted
ICDM
2003
IEEE
99views Data Mining» more  ICDM 2003»
15 years 8 months ago
Scalable Model-based Clustering by Working on Data Summaries
The scalability problem in data mining involves the development of methods for handling large databases with limited computational resources. In this paper, we present a two-phase...
Huidong Jin, Man Leung Wong, Kwong-Sak Leung
142
Voted
SDM
2007
SIAM
107views Data Mining» more  SDM 2007»
15 years 5 months ago
On Demand Phenotype Ranking through Subspace Clustering
High throughput biotechnologies have enabled scientists to collect a large number of genetic and phenotypic attributes for a large collection of samples. Computational methods are...
Xiang Zhang, Wei Wang 0010, Jun Huan
KDD
2012
ACM
185views Data Mining» more  KDD 2012»
13 years 6 months ago
A framework for summarizing and analyzing twitter feeds
The firehose of data generated by users on social networking and microblogging sites such as Facebook and Twitter is enormous. Real-time analytics on such data is challenging wit...
Xintian Yang, Amol Ghoting, Yiye Ruan, Srinivasan ...