Advertisement-Click Prediction Based on Mobile Big Data from HyXen AdLocus

  • Yu-Xiang Fei
  • Ji-Ying Chen
  • Shih-Hau Fang
  • Yu Tsao
  • Jen-Wei Huang
  • Bo-Wei Liang

Abstract

The popularity of Internet has made advertisement marketing gone virtualized and location-based mobile advertising successful in recent years. Adlocus, an APP developed by HyXen Technology, is one good example to achieve this. This advertising software can tailor to the campaign needs and target users within a diameter of 1 km. However, the question is that is it possible to predict whether the user is willing to click on the advertisement. This paper adopts many ways to analyze how these relations influence in different kinds of mobile advertisement. A comprehensive performance comparison of different models is provided, and the analysis of different factors is also discussed, including click time, advertisement category, language, and mobile phone manufacturers.

References

C. J. Wang and H. H. Chen, “Learning user behaviors for advertisements click prediction,” Proceedings of the 34rd international ACM SIGIR conference on research and development in information retrieval Workshop on Internet Advertising, 2011.

H. B. McMahan, et. al., “Ad click prediction: a view from the trenches,” Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013.

X. He, et al., “Practical lessons from predicting clicks on ads at facebook,” Proceedings of the Eighth International Workshop on Data Mining for Online Advertising, ACM, 2014.

Published
2016-10-01
How to Cite
Fei, Y.-X., Chen, J.-Y., Fang, S.-H., Tsao, Y., Huang, J.-W., & Liang, B.-W. (2016). Advertisement-Click Prediction Based on Mobile Big Data from HyXen AdLocus. Proceedings of Engineering and Technology Innovation, 4, 28-30. Retrieved from http://ojs.imeti.org/index.php/PETI/article/view/250
Section
Articles