Premium
A design for a common‐sense knowledge‐enhanced decision‐support system: Integration of high‐frequency market data and real‐time news
Author(s) -
Chen Kun,
Yin Jian,
Pang Sulin
Publication year - 2017
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/exsy.12209
Subject(s) - computer science , inference , common sense , decision support system , stock market , factor (programming language) , process (computing) , data science , data mining , knowledge management , artificial intelligence , paleontology , horse , biology , political science , law , programming language , operating system
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.