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Targeted Content Distribution in Outdoor Advertising Network by Learning Online User Behaviors

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Web and Wireless Geographical Information Systems (W2GIS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12473))

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Abstract

Digital outdoor advertising has revolutionized the way to display ads by allowing to deliver content dynamically. However, it is still a challenge to show the most suitable ad at the right time and place due to the spatio-temporal dynamics of human preferences. In this study, we attempt to realize smart digital billboards by mining mobile internet usage data, namely, for a given billboard, displaying the most relevant genre of ad at any given time. To achieve this goal, mobile internet usage data is applied as observations to train a state-sharing HMM. The hidden states, i.e., regional interests and preferences are learned, and the relative popularity of the states is then explored spatially and temporally. The regional preference dynamics are revealed by the learned state sequences. The discovered states and sequences of each region can be used to determine the most relevant ad genre to display. The proposed framework was successfully applied to Wuxue, a city in central China, as a case study.

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References

  1. Bauer, C., Dohmen, P., Strauss, C.: Interactive digital signage - an innovative service and its future strategies. In: Proceedings - 2011 International Conference on Emerging Intelligent Data and Web Technologies, EIDWT 2011, pp. 137–142. IEEE (2011)

    Google Scholar 

  2. Lai, J., Cheng, T., Lansley, G.: Improved targeted outdoor advertising based on geotagged social media data. Ann. GIS 23, 237–250 (2017). https://doi.org/10.1080/19475683.2017.1382571

    Article  Google Scholar 

  3. Zhang, X.L., Weng, W.G., Yuan, H.Y.: Empirical study of crowd behavior during a real mass event. J. Stat. Mech: Theory Exp. 2012, P08012 (2012)

    MATH  Google Scholar 

  4. Zhang, X.L., Weng, W.G., Yuan, H.Y., Chen, J.G.: Empirical study of a unidirectional dense crowd during a real mass event. Phys. A: Stat. Mech. Appl. 392, 2781–2791 (2013)

    Article  MathSciNet  Google Scholar 

  5. Okamoto, T., Sasaki, Y., Suzuki, S.: Targeted advertising using BLE beacon. In: 2017 IEEE 6th Global Conference on Consumer Electronics (GCCE), pp. 1–5. IEEE (2017)

    Google Scholar 

  6. JCDecaux: Dynamic content (2019). https://www.jcdecaux.com/brands/dynamic-content. Accessed 13 Dec 2019

  7. Longley, P.A., Adnan, M., Lansley, G.: The geotemporal demographics of Twitter usage. Environ. Plan. A 47, 465–484 (2015)

    Article  Google Scholar 

  8. Molitor, D., Reichhart, P., Spann, M.: Location-based advertising and contextual mobile targeting. In: 2016 International Conference on Information System, ICIS 2016 (2016)

    Google Scholar 

  9. Xia, T., Yu, Y., Xu, F., et al.: Understanding urban dynamics via state-sharing hidden Markov model. In: The World Wide Web Conference, pp. 3363–3369. ACM (2019)

    Google Scholar 

  10. Wang, T., Zhang, X., Wang, W.: Spatial-temporal distribution of mobile traffic and base station clustering based on urban function in cellular networks. In: Li, C., Mao, S. (eds.) WiCON 2017. LNICSSITE, vol. 230, pp. 300–312. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-90802-1_26

    Chapter  Google Scholar 

  11. Miao, Q., Qiao, Y., Yang, J.: Research of urban land use and regional functions based on mobile data traffic. In: 2018 IEEE Third International Conference on Data Science in Cyberspace (DSC), pp. 333–338. IEEE (2018)

    Google Scholar 

  12. Fang, Z., Yang, X., Xu, Y., et al.: Spatiotemporal model for assessing the stability of urban human convergence and divergence patterns. Int. J. Geogr. Inf. Sci. 31, 2119–2141 (2017)

    Article  Google Scholar 

  13. Xu, Y., Shaw, S.-L., Zhao, Z., et al.: Understanding aggregate human mobility patterns using passive mobile phone location data: a home-based approach. Transportation (Amst) 42, 625–646 (2015)

    Article  Google Scholar 

  14. Huang, M., Fang, Z., Xiong, S., Zhang, T.: Interest-driven outdoor advertising display location selection using mobile phone data. IEEE Access 7, 30878–30889 (2019). https://doi.org/10.1109/ACCESS.2019.2903277

    Article  Google Scholar 

  15. Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. Ser. B 39, 1–22 (1977)

    MathSciNet  MATH  Google Scholar 

  16. Viterbi, A.: Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Trans. Inf. Theory 13, 260–269 (1967)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan, 430079, People’s Republic of China

    Meng Huang & Zhixiang Fang

  2. Collaborative Innovation Center of Geospatial Technology, Wuhan, 430079, People’s Republic of China

    Zhixiang Fang

  3. China Mobile Group Hubei Company Limited, Wuhan, 430040, People’s Republic of China

    Tao Zhang

Authors
  1. Meng Huang
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  2. Zhixiang Fang
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  3. Tao Zhang
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Corresponding author

Correspondence to Zhixiang Fang .

Editor information

Editors and Affiliations

  1. University of Naples Federico II, Naples, Italy

    Sergio Di Martino

  2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

    Zhixiang Fang

  3. Department of Computer Science and Engineering, Pusan National University, Pusan, Korea (Republic of)

    Ki-Joune Li

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Huang, M., Fang, Z., Zhang, T. (2020). Targeted Content Distribution in Outdoor Advertising Network by Learning Online User Behaviors. In: Di Martino, S., Fang, Z., Li, KJ. (eds) Web and Wireless Geographical Information Systems. W2GIS 2020. Lecture Notes in Computer Science(), vol 12473. Springer, Cham. https://doi.org/10.1007/978-3-030-60952-8_13

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  • DOI: https://doi.org/10.1007/978-3-030-60952-8_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60951-1

  • Online ISBN: 978-3-030-60952-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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