基于RBR和CBR的金融事件本体推理研究

Ontology Reasoning for Financial Affairs with RBR and CBR

【目的】综合企业财务、非财务和舆情等因素预测金融事件对企业股价的影响,支持基于特定行业、特定金融事件主题之间的推理。【方法】基于本体的规则推理技术和案例推理技术,构建金融事件本体,设计基于本体的SWRL推理规则,采用Dloors引擎进行规则推理(RBR)。然后利用本体表示案例结构,建立基于本体的主题事件案例库,设计案例推理(CBR)表示、检索、重用、修正与保存模型。【结果】基于具体企业实例对规则推理和案例推理的结果进行验证,证明了本文所提推理模型的可靠性。【局限】本文重点在于金融本体及其推理模型的构建,股价预测是一种推理结果,故没有和其他股价预测方法进行定量比较。【结论】融合企业的舆情、财务和非财务指标,基于金融事件主题的案例推理和基于关联规则的规则推理模型,可以对大数据环境下企业股价进行预测。

[Objective]This paper tries to predict the impacts of financial events/news on stock price with financial,non-financial and public opinion factors.[Methods]We designed a financial affairs ontology based on the Rule-Based Reasoning(RBR)and Case-Based Reasoning(CBR).Then,we created a SWRL rule-based reasoning model,which pursued the rule-based reasoning using the Dloors engine.Thirdly,we designed a topic case database to describe the structure of the financial cases.Finally,we used the model to describe,retrieve,reuse,correct and preserve the data.[Results]We conducted an empirical study to examine the reliability of rule-based reasoning and case-based reasoning with enterprise data.[Limitations]We did not compare our model with the existing methods.[Conclusions]The proposed method could predict the stock price in big data environment.