Algorithm for online detection of data stream based on distance

• Published in: Ji suan ji ying yong yan jiu Vol. 32; no. 12; pp. 3579 - 3581
• Main Authors: Li, Shaobo, Wei, Zhonghe, Meng, Wei
• Format: Journal Article
• Language: Chinese
• Published: 01.12.2015
• Subjects: Algorithms; Data points; Data transmission; Dynamics; Online; Pruning; Sliding; Windows (intervals)
• DOI: 10.3969/j.issn.1001-3695.2015.12.011
• ISSN: 1001-3695

Aiming at the inaccuracy and high time complexity of traditional data stream mining technology, this paper introduced a new algorithm of date detection which based on k-distance to pruning and comentropy to detect in the sliding windows. This algorithm used the sliding windows to static dynamic data. When the data filled the current window, it used k-distance of the data to prune all the data in the preliminary testing. Then it filtered out the most of the normal data. At last it used comentropy to detect the remaining data which may be abnormal, output the data points whose comentropy was greater than the set threshold EA. The results of the experiments show that SWKC algorithm possess the better efficiency and accuracy than other some traditional detection algorithms.