Analysis of the prediction capability of web search data based on the HE-TDC method aEuro' prediction of the volume of daily tourism visitors

doi:10.1007/s11518-016-5311-7

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	Analysis of the prediction capability of web search data based on the HE-TDC method aEuro' prediction of the volume of daily tourism visitors
	Peng, Geng 1,2; Liu, Ying 1,2; Wang, Jiyuan 1,2; Gu, Jifa 3
	2017-04-01
发表期刊	JOURNAL OF SYSTEMS SCIENCE AND SYSTEMS ENGINEERING
ISSN	1004-3756
卷号	26 期号:2 页码:163-182
摘要	Web search query data are obtained to reflect social spots and serve as novel economic indicators. When faced with high-dimensional query data, selecting keywords that have plausible predictive ability and can reduce dimensionality is critical. This paper presents a new integrative method that combines Hurst Exponent (HE) and Time Difference Correlation (TDC) analysis to select keywords with powerful predictive ability. The method is called the HE-TDC screening method and requires keywords with predictive ability to satisfy two characteristics, namely, high correlation and fluctuation memorability similar to the predicting target series. An empirical study is employed to predict the volume of tourism visitors in the Jiuzhai Valley scenic area. The study shows that keywords selected using HE-TDC method produce a model with better robustness and predictive ability.
关键词	Tourism visitor volume prediction web-search data HE-TDC method Jiuzhai Valley time series Hurst exponent
DOI	10.1007/s11518-016-5311-7
语种	英语
资助项目	National Natural Science Foundation of China[71202115] ; National Natural Science Foundation of China[71172199] ; National Natural Science Foundation of China[71573244] ; National Natural Science Foundation of China[71532013] ; CCF-Tencent Open Research Fund[RAGR20150113] ; Key Project of the National Social Science Fund[14AZD044]
WOS研究方向	Operations Research & Management Science
WOS类目	Operations Research & Management Science
WOS记录号	WOS:000394023000002
出版者	SPRINGER HEIDELBERG
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/24772
专题	中国科学院数学与系统科学研究院
通讯作者	Liu, Ying
作者单位	1.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Key Lab Big Data Min & Knowledge Management, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Peng, Geng,Liu, Ying,Wang, Jiyuan,et al. Analysis of the prediction capability of web search data based on the HE-TDC method aEuro' prediction of the volume of daily tourism visitors[J]. JOURNAL OF SYSTEMS SCIENCE AND SYSTEMS ENGINEERING,2017,26(2):163-182.
APA	Peng, Geng,Liu, Ying,Wang, Jiyuan,&Gu, Jifa.(2017).Analysis of the prediction capability of web search data based on the HE-TDC method aEuro' prediction of the volume of daily tourism visitors.JOURNAL OF SYSTEMS SCIENCE AND SYSTEMS ENGINEERING,26(2),163-182.
MLA	Peng, Geng,et al."Analysis of the prediction capability of web search data based on the HE-TDC method aEuro' prediction of the volume of daily tourism visitors".JOURNAL OF SYSTEMS SCIENCE AND SYSTEMS ENGINEERING 26.2(2017):163-182.