Title :
A Discovery Method of Trend Rules from Complex Sequential Data
Author :
Sakurai, Shigeaki ; Makino, Kyoko ; Matsumoto, Shigeru
Author_Institution :
Adv. IT Lab., Toshiba Solutions Corp., Tokyo, Japan
Abstract :
This paper proposes a method that discovers trend rules from complex sequential data. The rules represent relationships among evaluation objects, keywords, and changes of numerical values related to the evaluation objects. The data is composed of numerical sequential data and text sequential data. The method extracts frequent patterns from transaction sets based on the changes. Also, it regards combinations of the patterns and the changes as trend rules. This paper applies the method to data sets composed of stock data and news headlines. Lastly, this paper compares the method with a method based on the random selection and shows the effect of the proposed method.
Keywords :
data mining; text analysis; complex sequential data; discovery method; frequent pattern extraction; news headlines; numerical sequential data; stock data; text sequential data; trend rules; Data mining; Earthquakes; Engines; Learning systems; Prediction methods; Stock markets; Training; Trend rule; evaluation object; frequent pattern; numerical sequential data; text sequential data;
Conference_Titel :
Advanced Information Networking and Applications Workshops (WAINA), 2012 26th International Conference on
Conference_Location :
Fukuoka
Print_ISBN :
978-1-4673-0867-0
DOI :
10.1109/WAINA.2012.21
