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ECML
2006
Springer
15 years 10 months ago
An Adaptive Kernel Method for Semi-supervised Clustering
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Bojun Yan, Carlotta Domeniconi
NIPS
2003
15 years 8 months ago
Pairwise Clustering and Graphical Models
Significant progress in clustering has been achieved by algorithms that are based on pairwise affinities between the datapoints. In particular, spectral clustering methods have ...
Noam Shental, Assaf Zomet, Tomer Hertz, Yair Weiss
ICDM
2009
IEEE
171views Data Mining» more  ICDM 2009»
15 years 4 months ago
Hybrid Clustering by Integrating Text and Citation Based Graphs in Journal Database Analysis
We propose a hybrid clustering strategy by integrating heterogeneous information sources as graphs. The hybrid clustering method is extended on the basis of modularity based Louva...
Xinhai Liu, Shi Yu, Yves Moreau, Frizo A. L. Janss...
210
Voted
ICASSP
2011
IEEE
14 years 10 months ago
A mutual information based approach for evaluating the quality of clustering
In this paper, a new method for evaluating the quality of clustering of genes is proposed based on mutual information criterion. Instead of using the conventional histogram-based ...
Shaikh Anowarul Fattah, Chia-Chun Lin, Sun-Yuan Ku...
KDD
2007
ACM
152views Data Mining» more  KDD 2007»
16 years 7 months ago
Efficient incremental constrained clustering
Clustering with constraints is an emerging area of data mining research. However, most work assumes that the constraints are given as one large batch. In this paper we explore the...
Ian Davidson, S. S. Ravi, Martin Ester