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SODA
2010
ACM
189views Algorithms» more  SODA 2010»
16 years 3 months ago
Correlation Clustering with Noisy Input
Correlation clustering is a type of clustering that uses a basic form of input data: For every pair of data items, the input specifies whether they are similar (belonging to the s...
Claire Mathieu, Warren Schudy
HICSS
2009
IEEE
122views Biometrics» more  HICSS 2009»
16 years 1 months ago
GrayWulf: Scalable Software Architecture for Data Intensive Computing
Big data presents new challenges to both cluster infrastructure software and parallel application design. We present a set of software services and design principles for data inte...
Yogesh Simmhan, Roger S. Barga, Catharine van Inge...
PAKDD
2009
ACM
115views Data Mining» more  PAKDD 2009»
16 years 1 months ago
Data Mining for Intrusion Detection: From Outliers to True Intrusions
Data mining for intrusion detection can be divided into several sub-topics, among which unsupervised clustering has controversial properties. Unsupervised clustering for intrusion...
Goverdhan Singh, Florent Masseglia, Céline ...
PKDD
2005
Springer
117views Data Mining» more  PKDD 2005»
15 years 11 months ago
A Bi-clustering Framework for Categorical Data
Bi-clustering is a promising conceptual clustering approach. Within categorical data, it provides a collection of (possibly overlapping) bi-clusters, i.e., linked clusters for both...
Ruggero G. Pensa, Céline Robardet, Jean-Fra...
JBI
2006
107views Bioinformatics» more  JBI 2006»
15 years 6 months ago
Knowledge guided analysis of microarray data
To microarray expression data analysis, it is well accepted that biological knowledge-guided clustering techniques show more advantages than pure mathematical techniques. In this ...
Zhuo Fang, Jiong Yang, Yixue Li, Qing-ming Luo, Le...