Adaptive filtering of advertisements on web pages
We present a browser extension to dynamically learn to filter unwanted images (such as advertisements or flashy graphics) based on minimal user feedback. To do so, we apply the weighted majority algorithm using pieces of the Uniform Resource Locators of such images as predictors. Experimental results tend to confirm that the accuracy of the predictions converges quickly to very high levels.
|Keywords||Advertisement filtering, Interface agents, Weighted majority|
|Conference||14th International World Wide Web Conference, WWW2005|
Esfandiari, B, & Nock, R. (Richard). (2005). Adaptive filtering of advertisements on web pages. Presented at the 14th International World Wide Web Conference, WWW2005. doi:10.1145/1062745.1062796