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- W2045905014 abstract "Cluster analysis is an important data mining issue, where objects under investigation are grouped into subsets of the original set of objects. In recent several years, a few clustering algorithms have been developed for the data stream problem. However these algorithms lack of extensibility or efficiency. In this paper we propose a new evolving data streams system with data fusion. We discuss a fundamentally different philosophy for data stream clustering which is guided by application centered requirements. The system is highly suitable for real-time implementation and is demonstrated through a series of experiments. The experiments over a number of real and synthetic data sets illustrate the effectiveness and efficiency." @default.
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- W2045905014 date "2012-08-01" @default.
- W2045905014 modified "2023-09-23" @default.
- W2045905014 title "A New Evolving Data Streams System with Data Fusion" @default.
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- W2045905014 doi "https://doi.org/10.1109/icicee.2012.461" @default.
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