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CIKM
2009
Springer
14 years 2 months ago
Fragment-based clustering ensembles
Clustering ensembles combine different clustering solutions into a single robust and stable one. Most of existing methods become highly time-consuming when the data size turns to ...
Ou Wu, Mingliang Zhu, Weiming Hu
DIS
2009
Springer
14 years 2 months ago
CHRONICLE: A Two-Stage Density-Based Clustering Algorithm for Dynamic Networks
Abstract. Information networks, such as social networks and that extracted from bibliographic data, are changing dynamically over time. It is crucial to discover time-evolving comm...
Min-Soo Kim 0002, Jiawei Han
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
14 years 8 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
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
SCIA
2005
Springer
186views Image Analysis» more  SCIA 2005»
14 years 1 months ago
Building Detection from Mobile Imagery Using Informative SIFT Descriptors
We propose reliable outdoor object detection on mobile phone imagery from off-the-shelf devices. With the goal to provide both robust object detection and reduction of computation...
Gerald Fritz, Christin Seifert, Manish Kumar, Luca...