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» Advances in constrained clustering
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KDD
2010
ACM
245views Data Mining» more  KDD 2010»
14 years 1 months ago
Flexible constrained spectral clustering
Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...
Xiang Wang, Ian Davidson
CIKM
2008
Springer
13 years 11 months ago
A consensus based approach to constrained clustering of software requirements
Managing large-scale software projects involves a number of activities such as viewpoint extraction, feature detection, and requirements management, all of which require a human a...
Chuan Duan, Jane Cleland-Huang, Bamshad Mobasher
WOB
2004
233views Bioinformatics» more  WOB 2004»
13 years 11 months ago
Recent Advances in Gene Expression Data Clustering: A Case Study with Comparative Results
Several advanced techniques have been proposed for data clustering and many of them have been applied to gene expression data, with partial success. The high dimensionality and the...
George Barreto Bezerra, Geraldo M. A. Cança...
KBSE
1999
IEEE
14 years 2 months ago
Advanced Modelling and Verification Techniques Applied to a Cluster File System
This paper describes the application of advanced formal modelling techniques and tools from the CADP toolset to the verification of CFS, a distributed file system kernel. After a ...
Charles Pecheur
PVLDB
2008
107views more  PVLDB 2008»
13 years 8 months ago
Constrained locally weighted clustering
Data clustering is a difficult problem due to the complex and heterogeneous natures of multidimensional data. To improve clustering accuracy, we propose a scheme to capture the lo...
Hao Cheng, Kien A. Hua, Khanh Vu