Analysis of the prediction capability of web searc

Authors: Geng Peng Ying Liu Jiyuan Wang Jifa Gu

Publish Date: 2017/01/24

Volume: 26, Issue: 2, Pages: 163-182

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Abstract

Web search query data are obtained to reflect social spots and serve as novel economic indicators When faced with highdimensional 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 HETDC 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 HETDC method produce a model with better robustness and predictive abilityGeng Peng received BS from North China Electric Power University in 1992 MS degree from Wuhan University of Science and Technology in 1998 and PhD degree from Tianjin University in 2001 Now he is an associate professor of School of Economic and Management University of Chinese Academy of Sciences UCAS He is having more than 15 years of teaching experience and current area of research includes ecommerce and Internet data analysisYing Liu received BS from Jilin University in 2006 MS and PhD degree from University of Chinese Academy of Sciences respectively in 2008 and 2011 Now he is an associate professor of School of Economic and Management UCAS His research interests focus on ecommerce Internet economy and Internet data analysisJifa Gu received his BS from Peking University and PhD from Institute of Mathematics USSR Academy He is a professor of Institute of Systems Science Chinese Academy of Sciences CAS He is academician of International Academy of Systems Science and Cybernetics His main interests are operations research systems engineering and systems science

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