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金融领域时间序列挖掘技术研究 被引量：5

A study of time series mining technology in financial field
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摘要 数据挖掘技术近年来被广泛用于时间序列分析,时间序列挖掘技术主要包括关联分析、序列分析、分类分析、聚类分析和异常检测等五类。由于金融领域的时间序列具有一些重要的特征,因此将各种挖掘方法与金融时间序列的特征,以及各种传统的时间序列分析模型相结合,是目前金融时间序列挖掘领域的研究热点。 Data mining technology is widely used in time series analysis.Time series mining includes association analysis,sequence analysis,classification,clustering and outlier detection.As financial time series has some important features,it has become a popular topic of research to combine features of various financial time series mining approaches with the traditional time series algorithms and analysis models.
作者 黄超 龚惠群
机构地区 东南大学经济管理学院 南京信息工程大学经济管理学院
出处 《东南大学学报（哲学社会科学版）》 CSSCI 2007年第5期36-39,共4页 Journal of Southeast University(Philosophy and Social Science)
基金 江苏省教育厅高校哲学社会科学研究指导项目"中国证券市场主要指数多标度分形相似性研究"(07SJD790052)成果之一
关键词 时间序列 金融 数据挖掘
分类号 F830 [经济管理—金融学] F224 [经济管理—国民经济]
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参考文献25

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二级参考文献35

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共引文献64

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二级引证文献19

东南大学学报（哲学社会科学版）
2007年 第5期

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