Building Wikipedia Ontology with More Semi-structured Information Resources

  • Tokio Kawakami
  • Takeshi Morita
  • Takahira Yamaguchi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10675)

Abstract

Wikipedia has been recently drawing attention as a semi-structured information resource for the automatic building of ontology. This paper describes a method of building general-purpose “lightweight ontology” by semi-automatically extracting the Is-a relation (rdfs:subClassOf), class-instance relation (rdf:type), concepts such as Triple, and a relation between concepts from information that includes category trees, define statements, lists and Wikipedia infoboxes. Also, we evaluate the built ontology by comparing it with other Wikipedia ontologies, such as YAGO and DBpedia.

Keywords

Ontologies Wikipedia Semi-structured information resource 

References

  1. [Suchanek 08]
    Suchanek, F.M., Kasneci, G., Weikum, G.: YAGO: a large ontology from Wikipedia and WordNet. J. Web Semant. 6(3), 203–217 (2008). ElsevierCrossRefGoogle Scholar
  2. [Hoffart 10]
    Hoffart, J., Suchanek, F., Berberich, K., Weikum, G.: YAGO2: a spatially and temporally enhanced knowledge base from Wikipedia, Research Report MPI-I-2010-5007. Max-Planck-Institut fur Informatik (2010)Google Scholar
  3. [Mahdisoltani 15]
    Mahdisoltani, F., Biega, J., Suchanek, F.M.: A knowledge base from multilingual Wikipedias. In: CIDR (2015)Google Scholar
  4. [Flati 14]
    Flati, T., Vannella, D., Pasini, T., Navigli, R.: Two Is Bigger (and Better) Than One: the Wikipedia Bitaxonomy Project, ACL (2014)Google Scholar
  5. [Melo 10]
    de Melo, G., Weikum, G.: MENTA: inducing multilingual taxonomies from Wikipedia. In: Proceedings of the 19th ACM International Conference on Information and Knowledge Management, pp. 1099–1108 (2010)Google Scholar
  6. [Kuhn 16]
    Kuhn, P., Mischkewitz, S., Ring, N., Windheuser, F.: Type inference on Wikipedia list pages, vol. P-259. LNI, pp. 2101–2111. GI (2016)Google Scholar
  7. [Gupta 16]
    Gupta, A., Piccinno, F., Kozhevnikov, M., Pasca, M., Pighin, D.: Revisiting taxonomy induction over Wikipedia. In: The 26th International Conference on Computational Linguistics (2016)Google Scholar
  8. [Ponzetto 07]
    Ponzetto, S.P., Strube, M.: Deriving a large scale taxonomy from Wikipedia. In: Proceedings of National Conference on Artificial Intelligence, pp. 1440–1447 (2007)Google Scholar
  9. [Wu 08]
    Wu, F., Weld, D.S.: Automatically refining the Wikipedia infobox ontology. In: Proceedings of the 17th International Conference on World Wide Web, pp. 635–644. ACM (2008)Google Scholar
  10. [Tamagawa 12]
    Tamagawa, S., Morita, T., Yamaguchi, T.: Extracting property semantics from Japanese Wikipedia. In: Huang, R., Ghorbani, A.A., Pasi, G., Yamaguchi, T., Yen, N.Y., Jin, B. (eds.) AMT 2012. LNCS, vol. 7669, pp. 357–368. Springer, Heidelberg (2012).  https://doi.org/10.1007/978-3-642-35236-2_36 CrossRefGoogle Scholar
  11. [Tamagawa 10]
    Tamagawa, S., Sakurai, S., Tejima, T., Morita, T., Izumi, N.: Learning a Large Scale of Ontology from Japanese Wikipedia, WI/IAT (2010)Google Scholar
  12. [Asano 16]
    Asano, H., Morita, T., Yamaguchi, T.: Development and evaluation of an operational service robot using Wikipedia-based and Domain Ontologies. In: Web Intelligence (2016)Google Scholar
  13. [Morita 14]
    Morita, T., Sekimoto, Y., Tamagawa, S., Yamaguchi, T.: Building up a class hierarchy with properties by refining and integrating Japanese Wikipedia Ontology and Japanese WordNet. Web Intell. Agent Syst. Int. J. 12(2), 211–233 (2014). IOS PressGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Tokio Kawakami
    • 1
  • Takeshi Morita
    • 1
  • Takahira Yamaguchi
    • 1
  1. 1.Keio UniversityYokohamaJapan

Personalised recommendations