Research of Detection Algorithm for Time Series Abnormal Subsequence  

作　　者：Chunkai Zhang Haodong Liu Ao Yin 

机构地区：[1]Department of Computer Science and Technology,Shenzhen Graduate School,Harbin Institute of Technology,Shenzhen,China

出　　处：《国际计算机前沿大会会议论文集》2017年第1期4-6,共3页International Conference of Pioneering Computer Scientists, Engineers and Educators（ICPCSEE）

摘　　要：The recent advancements in sensor technology have made it possible to collect enormous amounts of data in real time.How to find out unusual pattern from time series data plays a very important role in data mining.In this paper,we focus on the abnormal subsequence detection.The original definition of discord subsequences is defective for some kind of time series,in this paper we give a more robust definition which is based on the k nearest neighbors.We also donate a novel method for time series representation,it has better performance than traditional methods(like PAA/SAX)to represent the characteristic of some special time series.To speed up the process of abnormal subsequence detection,we used the clustering method to optimize the outer loop ordering and early abandon subsequence which is impossible to be abnormal.The experiment results validate that the algorithm is correct and has a high efficiency.

关 键 词：TIME SERIES REPRESENTATION ABNORMAL SUBSEQUENCE K nearest NEIGHBOR 

分 类 号：C5[社会学]