一种高效的基于相似性查找时间序列的位符号化表示方法*

到目前为止能够计算字符化时间序列的距离度量的方法很少，为此，提出了一种新的字符化的时间序列表示方法BSAP。该方法既能进行维度约简又允许在符号化后的时间序列表示法上定义距离度量。实验分别在合成数据和实际数据上进行，实验表明该方法具有更高的运算效率且需要较少的空间。

Novel binary symbolic representation of time series for similarity

In spite of there are dozens of techniques for producing different variants of the symbolic representation, there still have no known method to calculate the distance in the symbolic space to provide the lower bounding guarantee. This paper proposed a novel bit level symbolic representation called BSAP. The representation was unique in which it allowed dimensionality reduction and it also granted a lower bound distance measure defined on the symbolic representation. The experiments was performed on synthetic, as well as real data sequences to evaluate the proposed method.