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» Data Clustering: A Review
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ICML
2005
IEEE
16 years 7 months ago
Clustering through ranking on manifolds
Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-...
Markus Breitenbach, Gregory Z. Grudic
CIKM
2009
Springer
16 years 1 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
ECML
2007
Springer
16 years 24 days ago
Spectral Clustering and Embedding with Hidden Markov Models
Abstract. Clustering has recently enjoyed progress via spectral methods which group data using only pairwise affinities and avoid parametric assumptions. While spectral clustering ...
Tony Jebara, Yingbo Song, Kapil Thadani
KDD
2004
ACM
157views Data Mining» more  KDD 2004»
15 years 12 months ago
On detecting space-time clusters
Detection of space-time clusters is an important function in various domains (e.g., epidemiology and public health). The pioneering work on the spatial scan statistic is often use...
Vijay S. Iyengar
ACL
2008
15 years 8 months ago
When Specialists and Generalists Work Together: Overcoming Domain Dependence in Sentiment Tagging
This study presents a novel approach to the problem of system portability across different domains: a sentiment annotation system that integrates a corpus-based classifier trained...
Alina Andreevskaia, Sabine Bergler