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Abstract
New browser windows automatically appear without clicking them when certain web sites are browsed by a user. The user does not desire to open such browser windows but is forced to look at them. Such automatic displays of browser windows sometimes contain important announcements, system notices, web guidance, other related enclosure description, pop‐up advertisements and so on. Moreover, pop‐up advertising browser windows are efficient tools for advertisers. However, huge usage of such advertising has become excessive and caused annoyance for users. This study is to analyze and characterize whole web page syntax to create a trained model from Support Vector Machines to effectively discriminate between pop‐up advertisement browser windows and desirable browser windows. The experimental results show that the overall accuracy of the proposed pop‐up detector is up to 92.11%. Hence, it can really reduce annoyance for users.
Published Version
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