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» Data Clustering: A Review
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NCI
2004
142views Neural Networks» more  NCI 2004»
15 years 2 months ago
A competitive and cooperative learning approach to robust data clustering
This paper presents a new semi-competitive learning paradigm named Competitive and Cooperative Learning (CCL), in which seed points not only compete each other for updating to ada...
Yiu-ming Cheung
89
Voted
CSDA
2007
115views more  CSDA 2007»
15 years 18 days ago
Arbitrarily shaped multiple spatial cluster detection for case event data
An original method is proposed for spatial cluster detection of case event data. A selection order and the distance from the nearest neighbour are attributed to each point, once p...
Christophe Dematteï, Nicolas Molinari, Jean-P...
AIPRF
2008
15 years 2 months ago
A Coherent and Heterogeneous Approach to Clustering
Despite outstanding successes of the state-of-the-art clustering algorithms, many of them still suffer from shortcomings. Mainly, these algorithms do not capture coherency and homo...
Arian Maleki, Nima Asgharbeygi
84
Voted
ICPR
2008
IEEE
16 years 1 months ago
K-means clustering of proportional data using L1 distance
We present a new L1-distance-based k-means clustering algorithm to address the challenge of clustering high-dimensional proportional vectors. The new algorithm explicitly incorpor...
Bonnie K. Ray, Hisashi Kashima, Jianying Hu, Monin...
WWW
2007
ACM
16 years 1 months ago
A clustering method for web data with multi-type interrelated components
Traditional clustering algorithms work on "flat" data, making the assumption that the data instances can only be represented by a set of homogeneous and uniform features...
Levent Bolelli, Seyda Ertekin, Ding Zhou, C. Lee G...