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Real Time Prediction on Revisitation Behaviors of Short-Term Type Commodities

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Web Information Systems Engineering – WISE 2016 (WISE 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10041))

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Abstract

With the advent of Internet we have entered a new era, more and more enterprises take the network as the new profit growth point of the marketing channel. The target of network trading platform is to attract consumers firstly. In this paper, we first extract the five common features in customers’ visitation behaviors, i.e. commodity’s type popularity, commodity’s type revisitation ratio, user revisitation ratio, window repeat ratio and brand popularity. These features constitute the major factors that affect people’s short-term types of commodity revisitation behaviors. Based on features of revisitation behaviors, we propose method that can quickly predict consumers will have a types of commodity revisitation behavior. The method is based on Fuzzy Comprehensive Evaluation Method, namely FCEM-II. The experiment of our method adopts a large scale real and reliable data set, and the experimental results show that our proposed method are more accurate in the prediction tasks compared with the baselines.

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Acknowledgments

The research work was supported by the National Natural Science Foundation of China under Grant No. 61303005, No. 61572295, the Innovation Method Fund of China No. 2015IM010200, the Natural Science Foundation of Shandong Province of China under Grant No. ZR2014FM031, ZR2013FQ014, the Science and Technology Development Plan Project of Shandong Province No. 2015GGX101015, and the Shandong Province Independent Innovation Major Special Project No. 2015ZDJQ01002, No. 2015ZDXX0201B03.

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Authors and Affiliations

  1. School of Computer Science and Technology, Shandong University, Jinan, 250101, Shandong, People’s Republic of China

    Yuliang Shi, Shijun Liu & Lizhen Cui

  2. School of Software Engineering, Shandong University, Jinan, 250101, Shandong, People’s Republic of China

    Xiangzhen Xu, Jinghua Fu & Lizhen Cui

  3. Electronic Commerce Research Center of Shandong University, Jinan, 250101, Shandong, People’s Republic of China

    Lizhen Cui

Authors
  1. Xiangzhen Xu
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  2. Jinghua Fu
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  3. Yuliang Shi
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  4. Shijun Liu
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  5. Lizhen Cui
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Corresponding author

Correspondence to Lizhen Cui .

Editor information

Editors and Affiliations

  1. Poznań University of Economics, Poznan, Poland

    Wojciech Cellary

  2. University of Minnesota, Minneapolis, Minnesota, USA

    Mohamed F. Mokbel

  3. Tsinghua University, Beijing, China

    Jianmin Wang

  4. Victoria University, Melbourne, Victoria, Australia

    Hua Wang

  5. Victoria University, Melbourne, Victoria, Australia

    Rui Zhou

  6. Victoria University, Melbourne, Victoria, Australia

    Yanchun Zhang

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Xu, X., Fu, J., Shi, Y., Liu, S., Cui, L. (2016). Real Time Prediction on Revisitation Behaviors of Short-Term Type Commodities. In: Cellary, W., Mokbel, M., Wang, J., Wang, H., Zhou, R., Zhang, Y. (eds) Web Information Systems Engineering – WISE 2016. WISE 2016. Lecture Notes in Computer Science(), vol 10041. Springer, Cham. https://doi.org/10.1007/978-3-319-48740-3_26

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  • DOI: https://doi.org/10.1007/978-3-319-48740-3_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48739-7

  • Online ISBN: 978-3-319-48740-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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