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- W77243875 abstract "This paper presents an improved algorithm for partitioning clustering used for large data. The proposed method is based on the K-means algorithm which is commonly used because of easy implementation and easy control of time complexity when there are ’N’ number of documents, compared to other systems. Analysis on the performance of clustering experiments with an actual document data set, the proposed method obtained a performance of 8.8% higher than the randomly selected clustering in terms of center values. Furthermore, consistent clustering results were obtained by taking care of the dependency of clustering results on initial centers." @default.
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- W77243875 date "2012-01-01" @default.
- W77243875 modified "2023-09-26" @default.
- W77243875 title "Finding Good Initial Cluster Center by Using Maximum Average Distance" @default.
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- W77243875 doi "https://doi.org/10.1007/978-3-642-33983-7_23" @default.
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