Integrated approach of cognitive maps and neural networks using qualitative information on the World Wide Web: the KBNMiner

In this paper, we propose a method for integrating cognitive maps and neural networks to gain competitive advantage using qualitative information acquired from news information on the World Wide Web. We have developed the KBNMiner, which is designed to represent the knowledge of domain experts with cognitive maps, to search and retrieve news information on the Internet according to the knowledge and to apply the information to a neural network model. In addition, we investigate ways to train neural networks more effectively by separating the learning data into two groups on the basis of event information acquired from news information. To validate our proposed method, we applied 180,000 news articles to the KBNMiner. The experimental results are found to support our proposed method through tenfold cross-validation.
Publisher
BLACKWELL PUBL LTD
Issue Date
2004-11
Language
ENG
Keywords

TIME-SERIES; FORECASTING METHODS; GENETIC ALGORITHMS; DECISION-SUPPORT; KNOWLEDGE; SYSTEM; PERFORMANCE; PREDICTION; INDEX; ERROR

Citation

EXPERT SYSTEMS, v.21, no.5, pp.243 - 252

ISSN
0266-4720
DOI
10.1111/j.1468-0394.2004.00282.x
URI
http://hdl.handle.net/10203/3683
Appears in Collection
KGSF-Journal Papers(저널논문)
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