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Kernel Based K-Medoids for Clustering Data with Uncertainty
2010Uncertain data is ubiquitous in real-world applications due to various causes. In recent years, clustering uncertain data has been paid more attention by the research community, and the classical clustering algorithms based on partition, density and hierarchy have been extended to handle the uncertain data.
Baoguo Yang, Yang Zhang 0010
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A New and Efficient K-Medoid Algorithm for Spatial Clustering
2005A new k-medoids algorithm is presented for spatial clustering in large applications. The new algorithm utilizes the TIN of medoids to facilitate local computation when searching for the optimal medoids. It is more efficient than most existing k-medoids methods while retaining the exact the same clustering quality of the basic k-medoids algorithm.
Qiaoping Zhang, Isabelle Couloigner
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Sequential Nonparametric K-Medoid Clustering of Data Streams
2022 National Conference on Communications (NCC), 2022Sreeram C. Sreenivasan +1 more
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Clustering Time Series with k-Medoids Based Algorithms
2023Christopher Holder +2 more
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