Abstract
The problem of extracting structured data (i.e. lists, record sets, tables, etc.) from the Web has been traditionally approached by taking into account either the underlying markup structure of a Web page or the visual structure of the Web page. However, empirical results show that considering the HTML structure and visual cues of a Web page independently do not generalize well. We propose a new hybrid method to extract general lists from the Web. It employs both general assumptions on the visual rendering of lists, and the structural representation of items contained in them. We show that our method significantly outperforms existing methods across a varied Web corpus.
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Fumarola, F., Weninger, T., Barber, R., Malerba, D., Han, J. (2011). Extracting General Lists from Web Documents: A Hybrid Approach. In: Mehrotra, K.G., Mohan, C.K., Oh, J.C., Varshney, P.K., Ali, M. (eds) Modern Approaches in Applied Intelligence. IEA/AIE 2011. Lecture Notes in Computer Science(), vol 6703. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21822-4_29
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DOI: https://doi.org/10.1007/978-3-642-21822-4_29
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