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119
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SODA
2010
ACM
189views Algorithms» more  SODA 2010»
16 years 27 days 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
119
Voted
HICSS
2009
IEEE
122views Biometrics» more  HICSS 2009»
15 years 10 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...
131
Voted
GECCO
2003
Springer
114views Optimization» more  GECCO 2003»
15 years 8 months ago
Genetic Algorithm for Supply Planning Optimization under Uncertain Demand
Supply planning optimization is one of the most important issues for manufacturers and distributors. Supply is planned to meet the future demand. Under the uncertainty involved in ...
Masaru Tezuka, Masahiro Hiji
PAKDD
2009
ACM
115views Data Mining» more  PAKDD 2009»
15 years 10 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 ...
107
Voted
PKDD
2005
Springer
117views Data Mining» more  PKDD 2005»
15 years 9 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...