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» Finding Groups in Data: Cluster Analysis with Ants
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SAC
2004
ACM
15 years 5 months ago
Time-frequency feature detection for time-course microarray data
Gene clustering based on microarray data provides useful functional information to the working biologists. Many current gene-clustering algorithms rely on Euclidean-based distance...
Jiawu Feng, Paolo Emilio Barbano, Bud Mishra
SODA
2010
ACM
189views Algorithms» more  SODA 2010»
15 years 9 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
TSMC
2008
136views more  TSMC 2008»
14 years 11 months ago
Learning Relational Descriptions of Differentially Expressed Gene Groups
Abstract-- This paper presents a method that uses gene ontologies, together with the paradigm of relational subgroup discovery, to find compactly described groups of genes differen...
Igor Trajkovski, Filip Zelezný, Nada Lavrac...
CSCW
2012
ACM
13 years 7 months ago
Coordination and beyond: social functions of groups in open content production
We report on a study of the English edition of Wikipedia in which we used a mixed methods approach to understand how nested organizational structures called WikiProjects support c...
Andrea Forte, Niki Kittur, Vanessa Larco, Haiyi Zh...
GIS
2009
ACM
15 years 4 months ago
Conceptualization of place via spatial clustering and co-occurrence analysis
More and more users are contributing and sharing more and more contents on the Web via the use of content hosting sites and social media services. These user–generated contents ...
Dong-Po Deng, Tyng-Ruey Chuang, Rob Lemmens