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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
CEC
2005
IEEE
14 years 1 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
SIGIR
2003
ACM
14 years 1 months ago
Document clustering based on non-negative matrix factorization
In this paper, we propose a novel document clustering method based on the non-negative factorization of the termdocument matrix of the given document corpus. In the latent semanti...
Wei Xu, Xin Liu, Yihong Gong
SIGMOD
2000
ACM
165views Database» more  SIGMOD 2000»
14 years 5 days ago
Finding Generalized Projected Clusters In High Dimensional Spaces
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
Charu C. Aggarwal, Philip S. Yu
ERSHOV
2009
Springer
13 years 11 months ago
Indexing Dense Nested Metric Spaces for Efficient Similarity Search
Abstract. Searching in metric spaces is a very active field since it offers methods for indexing and searching by similarity in collections of unstructured data. These methods sele...
Nieves R. Brisaboa, Miguel Rodríguez Luaces...