RoadRunner: Towards Automatic Data Extraction from Large Web Sites
Proceedings of the 27th International Conference on Very Large Data Bases
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This work aims to provide a novel, site-specific web page segmentation and section importance detection algorithm, which leverages structural, content, and visual information. The structural and content information is leveraged via template, a generalized regular expression learnt over set of pages. The template along with visual information results into high sectioning accuracy. The experimental results demonstrate the effectiveness of the approach.