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20 October 2022 MDKI: a multi-relational dynamic stock forecasting model based on knowledge inference
Jiujiu Chen, Jinghua Tan, Junxiao Chen, Tongyi Guo, Tao Shu, Zhihao Gao
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Proceedings Volume 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022); 123501U (2022) https://doi.org/10.1117/12.2653334
Event: 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 2022, Qingdao, China
Abstract
The prediction of the stock price has been a complex issue. Here, we introduce a stock forecasting model based on a dynamic relationship that combines historical transaction data and knowledge extracted from news, which is mainly divided into subgraph and global relation learning two modules. The subgraph relationship is extracted from the existing industry classification and news information in the market, and the global learning module is based on the shared features between subgraphs and combines the attention mechanism to complete the prediction task. Experiments on the Chinese CSI100 stock and CSMAR news datasets show that our proposed model has certain effectiveness.
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Jiujiu Chen, Jinghua Tan, Junxiao Chen, Tongyi Guo, Tao Shu, and Zhihao Gao "MDKI: a multi-relational dynamic stock forecasting model based on knowledge inference", Proc. SPIE 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 123501U (20 October 2022); https://doi.org/10.1117/12.2653334
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KEYWORDS
Data modeling
Neural networks
Artificial intelligence
Convolution
Web 2.0 technologies
Statistical analysis
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