Next Generation of Data Mining in Finance

数据挖掘在金融应用上的未来

刘敏(Min Liu)

《Journal of Data Analysis》 6卷2期 (2011/04) Pp. 125-136

https://doi.org/10.6338/JDA.201104_6(2).0007

摘要

为了处理快速增长的海量数据，数据挖掘技术被广泛的应用于不同领域，而金融领域是其最具吸引力的应用领域之一。在过去，数据挖掘技术已广泛应用于股票市场预测、破产预测、信用风险评估、企业绩效预测等金融领域。这篇文章重点在于介绍数据挖掘在金融方面的新应用。计算机技术（如云计算技术）和数据库技术的快速发展，给数据挖掘带来了新的机遇和挑战。如何把新的计算机技术和数据库技术应用于金融数据挖掘，成为未来的数据挖掘在金融上应用的一个研究方向。与此同时，随着实务经验的增加，深入的具体应用理论会逐渐形成。这意味着，在未来，通过整合经验规律在不同领域的应用知识。将会有更加规范和精确的模型和方法应用于金融业的不同领域。

關鍵字

数据挖掘 ； 金融 ； 下一代

並列摘要

With the requirement to find methods to analysis the rapidly increasing data, as a branch of computer science, data mining technique has been widely apply in different domain .One of the most enticing application areas of data mining in these emerging technologies is in finance. To complete the financial tasks, data mining technique is used refer to Stock market forecasting, Bankruptcy Prediction, Credit Risk Estimation, Corporate Performance Prediction and Management Fraud. This paper focuses on new data mining applications in finance. The fast development of Compute technology (such as Cloud Computing) and database together gives data mining a new challenge and chance in data mining of finance. How to apply the new computer and database technique to the data mining, and integrate the previous framework and the new technology together to build a more efficiency and safer framework is a long way to go in the future . Meanwhile, after accumulate enough empirical regularity and experiences, deep field-specific theories will be set up. This means, in the future, it will have more standardized and accurate model and method to apply in different domain of finance by generating more empirical regularities and combining them with domain knowledge.

並列關鍵字

Data Mining ； Finance ； Next generation

參考文獻

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