A design for a common‐sense knowledge‐enhanced decision‐support system: Integration of high‐frequency market data and real‐time news |
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| Authors: | Kun Chen Jian Yin Sulin Pang |
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| Affiliation: | 1. Department of Finance, South University of Science and Technology of China, Shenzhen, China;2. College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China;3. School of Emergency Management, Jinan University, Guangzhou, China |
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| Abstract: | According to efficient markets theory, information is an important factor that affects market performance and serves as a source of first‐hand evidence in decision making, in particular with the rapid rise of Internet technologies in recent years. However, a lack of knowledge and inference ability prevents current decision support systems from processing the wide range of available information. In this paper, we propose a common‐sense knowledge‐supported news model. Compared with previous work, our model is the first to incorporate broad common‐sense knowledge into a decision support system, thereby improving the news analysis process through the application of a graphic random‐walk framework. Prototype and experiments based on Hong Kong stock market data have demonstrated that common‐sense knowledge is an important factor in building financial decision models that incorporate news information. |
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| Keywords: | decision support financial application knowledge engineering text mining |
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