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Link to original content: https://doi.org/10.1007/978-3-642-24826-9_15
Exploiting Attribute Redundancy for Web Entity Data Extraction | SpringerLink
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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7008))

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Abstract

Web entities are often associated with many attributes that describe them. It is essential to extract these attributes for Web entity data extraction. This paper proposes a novel approach using duplicated attribute value pairs. We start by constructing a initial seed set of attributes including names and enumerable values, and a training set of Web pages from target website; After that we locate the position of each attribute by matching attribute values within the pages of the site with values contained in the seed set; Thirdly we choose the position with the highest supportiveness as path for extraction, which we use to extract other attribute value pairs with the same template. Finally, we conduct an extensive experimental study with large real data set to demonstrate the effectiveness of our extraction approach.

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Zhu, Y., Yin, G., Li, X., Wang, H., Shi, D., Yuan, L. (2011). Exploiting Attribute Redundancy for Web Entity Data Extraction. In: Xing, C., Crestani, F., Rauber, A. (eds) Digital Libraries: For Cultural Heritage, Knowledge Dissemination, and Future Creation. ICADL 2011. Lecture Notes in Computer Science, vol 7008. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24826-9_15

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  • DOI: https://doi.org/10.1007/978-3-642-24826-9_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24825-2

  • Online ISBN: 978-3-642-24826-9

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