Similar subsequence retrieval from two time series data using homology search

We propose a method for extracting the most similar subsequences from two time series data by quantizing them and performing a homology search. The homology searches, such as BLAST and SW, are string search algorithms. Therefore, time series data should be quantized. SAX and EIAD were applied as quantization methods, and their effectiveness was examined by experiment. According to the experiments, time series data sets were classified into four types of time series data set, and we discuss the characteristics of SAX and EIAD.