M. Law, Carlos Sureda Gutiérrez, Nicolas Thome, Stéphane Gançarski
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Structural and visual similarity learning for Web page archiving
We present in this paper a Web page archiving approach combining image and structural techniques. Our main goal is to learn a similarity between Web pages in order to detect whether successive versions of pages are similar or not. Our system is based on a visual similarity measure designed for Web pages. Combined with a structural analysis of Web page source codes, a supervised feature selection method adapted to Web archiving is proposed. Experiments on real Web archives are reported including scalability issues.
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