Integrating Know-How into the Linked Data Cloud

  • Paolo Pareti
  • Benoit Testu
  • Ryutaro Ichise
  • Ewan Klein
  • Adam Barker
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8876)

Abstract

This paper presents the first framework for integrating procedural knowledge, or “know-how”, into the Linked Data Cloud. Know-how available on the Web, such as step-by-step instructions, is largely unstructured and isolated from other sources of online knowledge. To overcome these limitations, we propose extending to procedural knowledge the benefits that Linked Data has already brought to representing, retrieving and reusing declarative knowledge. We describe a framework for representing generic know-how as Linked Data and for automatically acquiring this representation from existing resources on the Web. This system also allows the automatic generation of links between different know-how resources, and between those resources and other online knowledge bases, such as DBpedia. We discuss the results of applying this framework to a real-world scenario and we show how it outperforms existing manual community-driven integration efforts.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Addis, A., Borrajo, D.: From Unstructured Web Knowledge to Plan Descriptions. In: Soro, A., Vargiu, E., Armano, G., Paddeu, G. (eds.) Information Retrieval and Mining in Distributed Environments. Studies in Computational Intelligence, vol. 324, pp. 41–59. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  2. 2.
    Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.G.: DBpedia: A Nucleus for a Web of Open Data. In: Aberer, K., Choi, K.-S., Noy, N., Allemang, D., Lee, K.-I., Nixon, L.J.B., Golbeck, J., Mika, P., Maynard, D., Mizoguchi, R., Schreiber, G., Cudré-Mauroux, P. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 722–735. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  3. 3.
    Fukazawa, Y., Ota, J.: Automatic Modeling of User’s Real World Activities from the Web for Semantic IR. In: Proceedings of the 3rd International Semantic Search Workshop, pp. 5:1–5:9 (2010)Google Scholar
  4. 4.
    Grüninger, M., Menzel, C.: The Process Specification Language (PSL) Theory and Applications. AI Magazine 24(3), 63–74 (2003)Google Scholar
  5. 5.
    Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA Data Mining Software: An Update. SIGKDD Explorer Newsletter 11(1), 10–18 (2009)CrossRefGoogle Scholar
  6. 6.
    Jung, Y., Ryu, J., Kim, K.-M., Myaeng, S.-H.: Automatic Construction of a Large-Scale Situation Ontology by Mining How-To Instructions from the Web. Web Semantics: Science, Services and Agents on the World Wide Web 8(2-3), 110–124 (2010)CrossRefGoogle Scholar
  7. 7.
    Kim, E., Helal, S., Cook, D.: Human Activity Recognition and Pattern Discovery. IEEE Pervasive Computing 9(1), 48–53 (2010)CrossRefGoogle Scholar
  8. 8.
    Martin, D., Burstein, M., Hobbs, J., Lassila, O., McDermott, D., McIlraith, S., Narayanan, S., Paolucci, M., Parsia, B., Payne, T., et al.: OWL-S: Semantic markup for web services. W3C member submission (2004)Google Scholar
  9. 9.
    Myaeng, S.-H., Jeong, Y., Jung, Y.: Experiential Knowledge Mining. Foundations and Trends in Web Science 4(1), 71–82 (2013)CrossRefGoogle Scholar
  10. 10.
    Pareti, P., Klein, E., Barker, A.: A Semantic Web of Know-how: Linked Data for Community-centric Tasks. In: Proceedings of the 23rd International Conference on World Wide Web Companion, pp. 1011–1016 (2014)Google Scholar
  11. 11.
    Perkowitz, M., Philipose, M., Fishkin, K., Patterson, D.J.: Mining Models of Human Activities from the Web. In: Proceedings of the 13th International Conference on World Wide Web, pp. 573–582 (2004)Google Scholar
  12. 12.
    Song, S.-k., Oh, H.-s., Myaeng, S.H., Choi, S.-p., Chun, H.-w., Choi, Y.-s., Jeong, C.-h.: Procedural Knowledge Extraction on MEDLINE Abstracts. In: Zhong, N., Callaghan, V., Ghorbani, A.A., Hu, B. (eds.) AMT 2011. LNCS, vol. 6890, pp. 345–354. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  13. 13.
    Tenorth, M., Klank, U., Pangercic, D., Beetz, M.: Web-Enabled Robots. IEEE Robotics Automation Magazine 18(2), 58–68 (2011)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Paolo Pareti
    • 1
    • 2
  • Benoit Testu
    • 1
  • Ryutaro Ichise
    • 1
  • Ewan Klein
    • 2
  • Adam Barker
    • 3
  1. 1.National Institute of InformaticsTokyoJapan
  2. 2.University of EdinburghEdinburghUnited Kingdom
  3. 3.University of St AndrewsSt AndrewsUnited Kingdom

Personalised recommendations