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• W2031098139 abstract "Affinity propagation clustering algorithm is with a broad value in science and engineering because of it no need to input the number of clusters in advances, robustness and good generalization. But the algorithm needs the initial similarity (the distance between any two points) as a parameter, a lot of time and storage space is required for the calculation of similarity. It's limited to apply to cluster of the large amounts of data. To solve problem, this paper brings forward K-AP cluster algorithm which integrate k-means algorithm to AP algorithm to decrease time-consuming and space superiority. The results show the KAP algorithm is faster than the original algorithm processing in speed, and it can cluster large amounts of data, and achieve better results." @default.
• W2031098139 created "2016-06-24" @default.
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• W2031098139 date "2011-09-01" @default.
• W2031098139 modified "2023-09-24" @default.
• W2031098139 title "K-AP Clustering Algorithm for Large Scale Dataset" @default.
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• W2031098139 doi "https://doi.org/10.1109/iwcdm.2011.28" @default.
• W2031098139 hasPublicationYear "2011" @default.
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