A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Personalising Mobile Advertising Based on Users' Installed Apps
2014
2014 IEEE International Conference on Data Mining Workshop
Mobile advertising is a billion pound industry that is rapidly expanding. The success of an advert is measured based on how users interact with it. In this paper we investigate whether the application of unsupervised learning and association rule mining could be used to enable personalised targeting of mobile adverts with the aim of increasing the interaction rate. Over May and June 2014 we recorded advert interactions such as tapping the advert or watching the whole advert video along with the
doi:10.1109/icdmw.2014.90
dblp:conf/icdm/RepsAGD14
fatcat:pwhea63zynbqrpjm7yzntr6mbe