DocumentCode :
3310181
Title :
A technical analysis expert system with knowledge refinement mechanism
Author :
Yamaguchi, Takahira ; Tachibana, Yoshiaki
Author_Institution :
Dept. of Comput. Sci., Shizuoka Univ., Japan
fYear :
1991
fDate :
9-11 Oct 1991
Firstpage :
86
Lastpage :
91
Abstract :
A refinement system is given which tries to refine a rule base, using task and domain strategies. In particular, the task strategy has domain-free rule primitives which are just relevant to generic tasks (signal processing or pattern recognition) and tries to move the initial rule space into a new better one, testing the applicability of new rule candidates in the new rule space with real data. An experiment on real Japanese stock-price data shows that a refined rule base almost has the same performance as one with top-level technical analysts in the Japanese stock market. This result implies that task and domain strategies would be essential refinement operators to move a rule space into a better one
Keywords :
expert systems; knowledge representation; stock markets; Japanese stock market; domain strategies; domain-free rule primitives; generic tasks; initial rule space; new rule candidates; pattern recognition; performance; real Japanese stock-price data; real data; refined rule base; refinement operators; refinement system; rule base; signal processing; task strategy; technical analysis expert system; top-level technical analysts; Computer science; Expert systems; Fluctuations; Humans; Knowledge engineering; Performance analysis; Refining; Signal processing; Stock markets; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence Applications on Wall Street, 1991. Proceedings., First International Conference on
Conference_Location :
New York, NY
Print_ISBN :
0-8186-2240-7
Type :
conf
DOI :
10.1109/AIAWS.1991.236568
Filename :
236568
Link To Document :
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