Discovering All-Chain Set in Streaming Time Series

摘要：

　　Time series chains discovery is an increasingly popular research area in time series mining.Previous studies on this topic process fixed-length time series.In this work,we focus on the issue of all-chain set mining over the streaming time series,where the all-chain set is a very important kind of the time series chains.We propose a novel all-chain set mining algorithm about streaming time series(ASMSTS)to solve this problem.The main idea behind the ASMSTS is to obtain the mining results at current time-tick based on the ones at the last one.This makes the method more efficiency in time and space than the Na(i)ve.Our experiments illustrate that ASMSTS does indeed detect the all-chain set correctly and can offer dramatic improvements in speed and space cost over the Naive method.

关键词： Streaming time series Time series chains All-chain set

作者: Shaopeng Wang Ye Yuan Hua Li

作者单位: Inner Mongolia University,Hohhot 010021,China Northeastern University,Shenyang 110819,China

会议类型: 国际会议

会议名称: The 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (第23届亚太知识发现和数据挖掘国际会议(PAKDD2019)

会议地点: 澳门

会议语种:英文

页码: 306-318

在线出版日期: 2019-04-14（万方平台首次上网日期，不代表论文的发表时间）