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» Approximate data mining in very large relational data
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KDD
2004
ACM
237views Data Mining» more  KDD 2004»
16 years 2 months ago
Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
Mario Medvedovic, Junhai Guo
200
Voted
SDM
2012
SIAM
285views Data Mining» more  SDM 2012»
13 years 4 months ago
A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets
Given the ubiquity of time series data, the data mining community has spent significant time investigating the best time series similarity measure to use for various tasks and dom...
Qiang Zhu 0002, Gustavo E. A. P. A. Batista, Thana...
DASFAA
2008
IEEE
190views Database» more  DASFAA 2008»
15 years 8 months ago
Analysis of Time Series Using Compact Model-Based Descriptions
Abstract. Recently, we have proposed a novel method for the compression of time series based on mathematical models that explore dependencies between different time series. This r...
Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...
ICDM
2003
IEEE
141views Data Mining» more  ICDM 2003»
15 years 7 months ago
Association Rule Mining in Peer-to-Peer Systems
We extend the problem of association rule mining – a key data mining problem – to systems in which the database is partitioned among a very large number of computers that are ...
Ran Wolff, Assaf Schuster
SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
14 years 4 months ago
Clustered low rank approximation of graphs in information science applications
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Berkant Savas, Inderjit S. Dhillon