Thomas Steiner and Stefan Mirea, SEKI@home, a Generic Approach for Crowdsourcing Knowledge Extraction from Arbitrary Web Pages, in Proceedings of the Semantic Web Challenge co-located with ISWC2012, Boston, US, November, 2012. [PDF(local)], [PDF(online)]

Abstract:
With SEKI@home, which stands for Search for Embedded Knowledge Items, we propose a generic, browser extension-based approach for crowdsourcing the task of knowledge extraction from arbitrary Web pages. As people with the extension installed browse a targeted Web page, the extension sends extracted knowledge items according to the customizable extraction rules to a centralized, optionally publicly accessible triple store. Thereby, simply by browsing the Web as usual, participants in the knowledge extraction task can help make previously locked-in knowledge openly accessible, e.g., via the standard SPARQL protocol. We have implemented and made available a prototype browser extension, which, after customization and adaptation, can serve as the basis for future knowledge extraction tasks.

BibTex:

    @InProceedings { iswc2012paper-semantic-web-challenge-btc-02,
      author = { Thomas Steiner and Stefan Mirea },
      title = { SEKI@home, a Generic Approach for Crowdsourcing Knowledge Extraction from Arbitrary Web Pages },
      booktitle = { Proceedings of the Semantic Web Challenge co-located with ISWC2012 },
      address = {Boston, US},
      month = { November },
      year = { 2012 },
    }

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