Maximizing Ad Revenue by Optimal Scheduling of Web Advertising
|International Journal of Computer Science and Engineering|
|© 2019 by SSRG - IJCSE Journal|
|Volume 6 Issue 3|
|Year of Publication : 2019|
|Authors : Mr.J.Ganesh M.E|
How to Cite?
Mr.J.Ganesh M.E, "Maximizing Ad Revenue by Optimal Scheduling of Web Advertising," SSRG International Journal of Computer Science and Engineering , vol. 6, no. 3, pp. 1-5, 2019. Crossref, https://doi.org/10.14445/23488387/IJCSE-V6I3P101
WWW is very popular today. So many advertisers place their advertisements in web site in order to maximize the revenue. So we need an algorithm that must be optimal to place the ads. So we propose a model known as Hybrid model, where price is a function of 1) number of time the ad is exposed and 2) number of times the ad is clicked. Using this Hybrid model, I proposed two versions of solution. First one is a static where ads statically placed for some periodic time. It doesn’t consider the user click behavior. Second one is dynamic where the schedule of ads is changed based in individual user click behavior. To obtain the second solution, we always maintain a parameter known as click probability. The user click behavior during a visit is observed and this information is exploited in scheduling. But in the static version, click events are not observed, and scheduling decisions are therefore made based upon the total expected click probability. As a result, a schedule that adapts to the user click behavior consistently outperforms the static solution.
CPM, CTM, HM
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