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» Scalable Model-based Clustering by Working on Data Summaries
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CIKM
2009
Springer
14 years 2 months ago
Scalable learning of collective behavior based on sparse social dimensions
The study of collective behavior is to understand how individuals behave in a social network environment. Oceans of data generated by social media like Facebook, Twitter, Flickr a...
Lei Tang, Huan Liu
CSB
2003
IEEE
150views Bioinformatics» more  CSB 2003»
14 years 24 days ago
Algorithms for Bounded-Error Correlation of High Dimensional Data in Microarray Experiments
The problem of clustering continuous valued data has been well studied in literature. Its application to microarray analysis relies on such algorithms as -means, dimensionality re...
Mehmet Koyutürk, Ananth Grama, Wojciech Szpan...
EUROPAR
2004
Springer
14 years 27 days ago
From Heterogeneous Task Scheduling to Heterogeneous Mixed Parallel Scheduling
Abstract. Mixed-parallelism, the combination of data- and taskparallelism, is a powerful way of increasing the scalability of entire classes of parallel applications on platforms c...
Frédéric Suter, Frederic Desprez, He...
ADMA
2005
Springer
202views Data Mining» more  ADMA 2005»
13 years 9 months ago
A Latent Usage Approach for Clustering Web Transaction and Building User Profile
Web transaction data between web visitors and web functionalities usually convey users’ task-oriented behavior patterns. Clustering web transactions, thus, may capture such infor...
Yanchun Zhang, Guandong Xu, Xiaofang Zhou
TKDE
2012
190views Formal Methods» more  TKDE 2012»
11 years 10 months ago
Scalable Learning of Collective Behavior
—This study of collective behavior is to understand how individuals behave in a social networking environment. Oceans of data generated by social media like Facebook, Twitter, Fl...
Lei Tang, Xufei Wang, Huan Liu