Abstract
Reading is an activity which takes place widely on the web: almost all newspapers have his own digital version on the internet and there are even a lot of magazines only on the web. In such a scenario, Computer Vision can offer a useful set of tools that can help web editors to improve the quality of the provided service. One of these tools is here presented: given a webpage of a newspaper or journal, the proposed framework localizes news items remotely clicked by users, giving the bounding box of the content of an article in its relative homepage. The tool is hence able to track an article in the page in which is contained at any time during the day: such an information is very useful for web editors to understand the trend of the published items and to rearrange the contents of the homepage accordingly.
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Notes
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Moltisanti, D., Farinella, G.M., Battiato, S., Giuffrida, G. (2016). Web Scraping of Online Newspapers via Image Matching. In: Russo, G., Capasso, V., Nicosia, G., Romano, V. (eds) Progress in Industrial Mathematics at ECMI 2014. ECMI 2014. Mathematics in Industry(), vol 22. Springer, Cham. https://doi.org/10.1007/978-3-319-23413-7_4
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DOI: https://doi.org/10.1007/978-3-319-23413-7_4
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