An Approach to Linguistic Summarization based on Comparison among Multiple Time-series Data

被引：0

作者：

Kobayashi, Mizuki ^{[1
]}

Kobayashi, Ichiro ^{[1
]}

机构：

[1] Ochanomizu Univ, Fac Sci, Grad Sch Humanities & Sci, Adv Sci,Bunkyo Ku, 2-1-1 Ohtsuka, Tokyo 1128610, Japan

来源：

6TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS, AND THE 13TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS | 2012年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a method of linguistic summarization of the relation among multiple time-series data by comparing them. The relation among the data is found by correlation coefficient and then it is categorized into main three relations: (i) similar trends, (ii) symmetrical trends, and (iii) non-correlation. Symbolic Aggregate approximation (SAX) is applied to the data categorized into these three types for coding numerical data, and then significant points of two time-series data are extracted by our modified edit distance.

引用

页码：1100 / 1103

页数：4