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Kizomba: An Unsupervised Heuristic-Based Web Information Extractor

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Trends in Practical Applications of Scalable Multi-Agent Systems, the PAAMS Collection (PAAMS 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 473))

Abstract

The Web is an ever growing repository of valuable information. That information lacks semantics since it is buried into web documents that are represented using HTML. Information extractors are software components that help software engineers in the task of extracting structured information from web documents.

This work was supported by the European Commission (FEDER) and the Spanish R&D&I programme by means of grant TIN2013-40848-R.

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References

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Correspondence to Juan C. Roldán .

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Roldán, J.C. (2016). Kizomba: An Unsupervised Heuristic-Based Web Information Extractor. In: de la Prieta, F., et al. Trends in Practical Applications of Scalable Multi-Agent Systems, the PAAMS Collection. PAAMS 2016. Advances in Intelligent Systems and Computing, vol 473. Springer, Cham. https://doi.org/10.1007/978-3-319-40159-1_35

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  • DOI: https://doi.org/10.1007/978-3-319-40159-1_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40158-4

  • Online ISBN: 978-3-319-40159-1

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