关键词: 数据挖掘, 时间序列, 自适应, 分段线性表示

Abstract: Time series is an important high dimension data type composed of a series of data observed according to time sequence.Usually time series data is massive.Sometimes，it is inefficient or impractical to mine the original time-series data directly.So time series should be represented on a higher level.Reference to the idea of piecewise linear of time series，we put forward a method of adaptive piecewise linear representation of time series based on error restricted.This method can give the number of fitting lines automatically according to a given error e on the special points of time series，This method not only compresses data and wipes of noise，but also finds the various pattern features of time series.According to experiments our algorithm leads to less fitting error and better performance than other algorithms.

Key words: data mining, time series, adaptive, piecewise linear representation