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AIPRF
2008
13 years 8 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
COMPGEOM
2004
ACM
14 years 24 days ago
A scalable simulator for forest dynamics
Models of forest ecosystems are needed to understand how climate and land-use change can impact biodiversity. In this paper we describe an individual-based, spatially-explicit for...
Sathish Govindarajan, Mike Dietze, Pankaj K. Agarw...
GECCO
2008
Springer
171views Optimization» more  GECCO 2008»
13 years 8 months ago
Particle swarm clustering ensemble
Extracting natural groups of the unlabeled data is known as clustering. To improve the stability and robustness of the clustering outputs, clustering ensembles have emerged recent...
Abbas Ahmadi, Fakhri Karray, Mohamed Kamel
TKDE
2008
197views more  TKDE 2008»
13 years 7 months ago
Agglomerative Fuzzy K-Means Clustering Algorithm with Selection of Number of Clusters
In this paper, we present an agglomerative fuzzy K-Means clustering algorithm for numerical data, an extension to the standard fuzzy K-Means algorithm by introducing a penalty term...
Mark Junjie Li, Michael K. Ng, Yiu-ming Cheung, Jo...
ICAI
2004
13 years 8 months ago
K-medoid-style Clustering Algorithms for Supervised Summary Generation
This paper centers on the discussion of k-medoid-style clustering algorithms for supervised summary generation. This task requires clustering techniques that identify class-unifor...
Nidal M. Zeidat, Christoph F. Eick