带弱通配符的模式匹配及其在时序分析中的应用

摘要

针对模式匹配的准确性和灵活性问题,提出了一种基于弱通配符的匹配算法,以快速定位重要的时间点,辅助用户决策.首先通过数据预处理得到编码字符串序列,然后定义具有特殊语义的弱通配符及区间长度,最后设计一种高效的模式匹配算法.在时序分析中,模式反映了数据的变化趋势,预示着事件的发生.传统的精确匹配受噪声的影响比较大,匹配的灵活性低.通过添加弱通配符可以兼顾匹配过程的灵活性和准确性.油田产量与股票交易数据实验表明,所提方法较精确匹配而言,能够更有效地找到符合用户要求的模式.%This paper proposed a pattern matching method based on weak-wildcards to obtain accurate and flexible matching which is good for locating critical time points and assisting users' decision.First,a nominal sequence was obtained through coding the time series.Second,the concepts of weak-wildcard and gaps with special semantics were defined.Third,an efficient pattern matching algorithm was designed.In time series analysis,patterns reflect the trend of data change and indicate the occurrence of events.The traditional exact pattern matching is greatly affected by the noise,which has lower matching flexibility.Adding weak-wildcards gives consideration to both accuracy and flexibility.Experiments were undertaken on oil production and stock transaction data.Results show that compared to exact pattern matching method,the proposed pattern matching method copes with users' expectation better.