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- W80032026 abstract "A successive partial cluster algorithm for large data sets is proposed in this paper. In each iteration of this algorithm, only a new cluster is generated by successive iteration method. Firstly, typical point was selected successively based on sampling density and then cluster is constructed by using this typical point as seed. When the first cluster is produced, those data items contained by this cluster are deleted timely. Repeat this process until the remaining data set is small enough to read into memory. The rest of the data items are assigned to the nearest cluster respectively. The effective of this algorithm is verified by several experiments." @default.
- W80032026 created "2016-06-24" @default.
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- W80032026 date "2010-01-01" @default.
- W80032026 modified "2023-09-25" @default.
- W80032026 title "An Efficient Successive Iteration Partial Cluster Algorithm for Large Datasets" @default.
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- W80032026 doi "https://doi.org/10.1007/978-3-642-14880-4_61" @default.
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