Abstract
Traditional text-based web page similarity measures fail to handle rich-information-embedded modern web pages. Current approaches regard web pages as either DOM trees or images. However, the former only focuses on the web page structure, while the latter ignores the inner connections among different web page features. Therefore, they are not suitable for modern web pages. Hence, the idea of a block tree is introduced, which contains both structural and visual information of web pages. A visual similarity metric is proposed as the edit distance between two block trees. Finally, an experiment is undertaken, by cross-comparing 500 web pages, illustrating that the model appears to be highly accurate, empirically demonstrating that the metric is highly promising.
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