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» Clustering Improves the Exploration of Graph Mining Results
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PRL
2002
67views more  PRL 2002»
14 years 11 months ago
A pseudo-nearest-neighbor approach for missing data recovery on Gaussian random data sets
Missing data handling is an important preparation step for most data discrimination or mining tasks. Inappropriate treatment of missing data may cause large errors or false result...
Xiaolu Huang, Qiuming Zhu
PAISI
2010
Springer
14 years 9 months ago
Efficient Privacy Preserving K-Means Clustering
Abstract. This paper introduces an efficient privacy-preserving protocol for distributed K-means clustering over an arbitrary partitioned data, shared among N parties. Clustering i...
Maneesh Upmanyu, Anoop M. Namboodiri, Kannan Srina...
JDWM
2006
178views more  JDWM 2006»
14 years 12 months ago
Improved Data Partitioning for Building Large ROLAP Data Cubes in Parallel
The pre-computation of data cubes is critical to improving the response time of On-Line Analytical Processing (OLAP) systems and can be instrumental in accelerating data mining ta...
Ying Chen, Frank K. H. A. Dehne, Todd Eavis, Andre...
BMCBI
2011
14 years 3 months ago
Clustering gene expression data with a penalized graph-based metric
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
Ariel E. Bayá, Pablo M. Granitto
AI
2006
Springer
14 years 12 months ago
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Ole J. Mengshoel, David C. Wilkins, Dan Roth