• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science

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Detecting outliers in data stream based on grid coupling 

YANG Jie,ZHANG Dong-yue,ZHOU Li-hua,HUANG Hao,DING Hai-yan     

  1.   (School of Information Science & Engineering,Yunnan University,Kunming 650504,China)
  • Received:2019-09-09 Revised:2019-11-04 Online:2020-01-25 Published:2020-01-25

Abstract:

The grid-based data analysis method processes data in units of grids, avoiding the point-to-point calculation of data objects and greatly improving the efficiency of data analysis. However, the traditional grid-based method processes the grid independently in the analysis process, ignoring the coupling relationship between the grids and resulting in unsatisfactory analysis accuracy. In this paper, the grids are no longer processed independently and the coupling relationship between grids are considered, when the grids are used to detect outliers in data stream. A grid coupling based outliers detection algorithm for data streams (GCStream-OD) is proposed. The algorithm exactly expresses the correlation between data stream objects through grid coupling, and improves the efficiency of the algorithm through pruning strategy. Experimental results on five real data streams show that GCStream-OD has higher quality and efficiency of outliers detection.
 

Key words: outliers detection, data stream, grid coupling