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157
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TALG
2010
158views more  TALG 2010»
14 years 10 months ago
Clustering for metric and nonmetric distance measures
We study a generalization of the k-median problem with respect to an arbitrary dissimilarity measure D. Given a finite set P of size n, our goal is to find a set C of size k such t...
Marcel R. Ackermann, Johannes Blömer, Christi...
166
Voted
KDD
2009
ACM
188views Data Mining» more  KDD 2009»
16 years 4 months ago
Mining discrete patterns via binary matrix factorization
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
Bao-Hong Shen, Shuiwang Ji, Jieping Ye
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 4 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
150
Voted
ICDM
2009
IEEE
148views Data Mining» more  ICDM 2009»
15 years 10 months ago
Online System Problem Detection by Mining Patterns of Console Logs
Abstract—We describe a novel application of using data mining and statistical learning methods to automatically monitor and detect abnormal execution traces from console logs in ...
Wei Xu, Ling Huang, Armando Fox, David Patterson, ...
ISI
2007
Springer
15 years 10 months ago
Mining Higher-Order Association Rules from Distributed Named Entity Databases
The burgeoning amount of textual data in distributed sources combined with the obstacles involved in creating and maintaining central repositories motivates the need for effective ...
Shenzhi Li, Christopher D. Janneck, Aditya P. Bela...