An Automated Framework with Application to Study Url Based Online Advertisements Detection

Piotr Lech Szczepański , Adrian Wiśniewski , Tomasz Gerszberg


A rapid growth of online advertisements results in unsolicited bulk of data being downloaded during web surfing. To tackle this problem a fast mechanism detecting adverts is required. In this paper we present the usefulness of URL based web-pages classification in the process of online advertisements detection. Our experiments are performed on seven popular classifiers using the real-life dataset obtained by human agents browsing the internet. We introduce a general and fully automated framework that allows us to do a comprehensive analysis by performing simultaneously hundreds of experiments. This study results in solution with 0.987 accuracy and 0.822 F-measure.
Author Piotr Lech Szczepański (FEIT / IN)
Piotr Lech Szczepański,,
- The Institute of Computer Science
, Adrian Wiśniewski (FEIT / IN)
Adrian Wiśniewski,,
- The Institute of Computer Science
, Tomasz Gerszberg
Tomasz Gerszberg,,
Journal seriesJournal of Applied Mathematics, Statistics and Informatics, ISSN 1336-9180
Issue year2013
Languageen angielski
Score (nominal)0
ScoreMinisterial score = 0.0, 27-03-2017, ArticleFromJournal
Ministerial score (2013-2016) = 0.0, 27-03-2017, ArticleFromJournal
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