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» Clustering-Based K-Anonymisation Algorithms
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KDD
2004
ACM
132views Data Mining» more  KDD 2004»
15 years 10 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
82
Voted
SDM
2009
SIAM
223views Data Mining» more  SDM 2009»
15 years 6 months ago
Context Aware Trace Clustering: Towards Improving Process Mining Results.
Process Mining refers to the extraction of process models from event logs. Real-life processes tend to be less structured and more flexible. Traditional process mining algorithms...
R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aa...
68
Voted
CEC
2005
IEEE
15 years 3 months ago
Improvements to the scalability of multiobjective clustering
In previous work, we have proposed a novel approach to data clustering based on the explicit optimization of a partitioning with respect to two complementary clustering objectives ...
Julia Handl, Joshua D. Knowles
OTM
2005
Springer
15 years 3 months ago
Web Image Semantic Clustering
This paper provides a novel Web image clustering methodology based on their associated texts. In our approach, the semantics of Web images are firstly represented into vectors of t...
Zhiguo Gong, Leong Hou U, Chan Wa Cheang
AIRS
2004
Springer
15 years 3 months ago
Automatic Word Clustering for Text Categorization Using Global Information
This paper presents a cluster-based text categorization system which uses class distributional clustering of words. We propose a new clustering model which considers the global in...
Wenliang Chen, Xingzhi Chang, Huizhen Wang, Jingbo...