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.

Additional Metadata
Keywords Advertisement filtering, Interface agents, Weighted majority
Persistent URL dx.doi.org/10.1145/1062745.1062796
Conference 14th International World Wide Web Conference, WWW2005
Citation
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