Encyclopedic Knowledge Patterns from Wikipedia Links

  • Andrea Giovanni Nuzzolese
  • Aldo Gangemi
  • Valentina Presutti
  • Paolo Ciancarini
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7031)


What is the most intuitive way of organizing concepts for describing things? What are the most relevant types of things that people use for describing other things? Wikipedia and Linked Data offer knowledge engineering researchers a chance to empirically identifying invariances in conceptual organization of knowledge i.e. knowledge patterns. In this paper, we present a resource of Encyclopedic Knowledge Patterns that have been discovered by analyizing the Wikipedia page links dataset, describe their evaluation with a user study, and discuss why it enables a number of research directions contributing to the realization of a meaningful Semantic Web.


User Study Object Type Relevance Score Subject Type Triple Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Akbik, A., Broß, J.: Wanderlust: Extracting Semantic Relations from Natural Language Text Using Dependency Grammar Patterns. In: Proc. of the Workshop on Semantic Search (SemSearch 2009) at the 18th International World Wide Web Conference (WWW 2009), Madrid, Spain, pp. 6–15 (2009)Google Scholar
  2. 2.
    Baker, C.F., Fillmore, C.J., Lowe, J.B.: The Berkeley FrameNet Project. In: Proc. of the 17th International Conference on Computational Linguistics, Morristown, NJ, USA, pp. 86–90 (1998)Google Scholar
  3. 3.
    Blomqvist, E., Presutti, V., Gangemi, A.: Experiments on pattern-based ontology design. In: Proceeding of K-CAP 2009, Redondo Beach, California, USA, pp. 41–48. ACM (2009)Google Scholar
  4. 4.
    Blomqvist, E., Sandkuhl, K., Scharffe, F., Svatek, V.: Proc. of the Workshop on Ontology Patterns (WOP, collocated with the 8th International Semantic Web Conference (ISWC-2009), Washington D.C., USA. CEUR Workshop Proceedings, vol. 516 (October 25 (2009)Google Scholar
  5. 5.
    Gangemi, A., Presutti, V.: Towards a Pattern Science for the Semantic Web. Semantic Web 1(1-2), 61–68 (2010)Google Scholar
  6. 6.
    Giuliano, C., Gliozzo, A.M., Gangemi, A., Tymoshenko, K.: Acquiring Thesauri from Wikis by Exploiting Domain Models and Lexical Substitution. In: Aroyo, L., Antoniou, G., Hyvönen, E., ten Teije, A., Stuckenschmidt, H., Cabral, L., Tudorache, T. (eds.) ESWC 2010. LNCS, vol. 6089, pp. 121–135. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  7. 7.
    Gruninger, M., Fox, M.S.: The role of competency questions in enterprise engineering. In: Proc. of the IFIP WG5.7 Workshop on Benchmarking - Theory and Practice, Trondheim, Norway, pp. 83–95 (1994)Google Scholar
  8. 8.
    Lehmann, J., Bizer, C., Kobilarov, G., Auer, S., Becker, C., Cyganiak, R., Hellmann, S.: DBpedia - A Crystallization Point for the Web of Data. Journal of Web Semantics 7(3), 154–165 (2009)CrossRefGoogle Scholar
  9. 9.
    Medelyan, O., Milne, D., Legg, C., Witten, I.H.: Mining meaning from wikipedia. Int. J. Hum.-Comput. Stud. 67(9), 716–754 (2009)CrossRefGoogle Scholar
  10. 10.
    Migliore, M., Novara, G., Tegolo, D.: Single neuron binding properties and the magical number 7. Hippocampus 18(11), 1122–1130 (2008)CrossRefGoogle Scholar
  11. 11.
    Miller, G.A.: The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychological Review 63(2), 81–97 (1956)CrossRefGoogle Scholar
  12. 12.
    Nastase, V., Strube, M., Boerschinger, B., Zirn, C., Elghafari, A.: WikiNet: A Very Large Scale Multi-Lingual Concept Network. In: Calzolari, N., Choukri, K., Maegaard, B., Mariani, J., Odijk, J., Piperidis, S., Rosner, M., Tapias, D. (eds.) Proc. of the Seventh International Conference on Language Resources and Evaluation (LREC), pp. 1015–1022. European Language Resources Association (2010)Google Scholar
  13. 13.
    Nguyen, D.P.T., Matsuo, Y., Ishizuka, M.: Relation extraction from wikipedia using subtree mining. In: Proc. of the 22nd National Conference on Artificial Intelligence, vol. 2, pp. 1414–1420. AAAI Press (2007)Google Scholar
  14. 14.
    Nuzzolese, A.G., Gangemi, A., Presutti, V.: Gathering Lexical Linked Data and Knowledge Patterns from FrameNet. In: Proc. of the 6th International Conference on Knowledge Capture (K-CAP), Banff, Alberta, Canada, pp. 41–48 (2011)Google Scholar
  15. 15.
    Ponzetto, S.P., Navigli, R.: Large-Scale Taxonomy Mapping for Restructuring and Integrating Wikipedia.. In: Boutilier, C. (ed.) IJCAI, Pasadena, USA, pp. 2083–2088 (2009)Google Scholar
  16. 16.
    Presutti, V., Chaudhri, V.K., Blomqvist, E., Corcho, O., Sandkuhl, K.: Proc. of the Workshop on Ontology Patterns (WOP 2010) at ISWC-2010, Shangai, China. CEUR Workshop Proceedings (November 8, 2010)Google Scholar
  17. 17.
    Singh, P.: The Open Mind Common Sense project. Technical report, MIT Media Lab (2002)Google Scholar
  18. 18.
    Suchanek, F., Kasneci, G., Weikum, G.: Yago - A Large Ontology from Wikipedia and WordNet. Elsevier Journal of Web Semantics 6(3), 203–217 (2008)CrossRefGoogle Scholar
  19. 19.
    Völker, J., Niepert, M.: Statistical Schema Induction. In: Antoniou, G., Grobelnik, M., Simperl, E., Parsia, B., Plexousakis, D., De Leenheer, P., Pan, J. (eds.) ESWC 2011, Part I. LNCS, vol. 6643, pp. 124–138. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  20. 20.
    Zesch, T., Müller, C., Gurevych, I.: Extracting Lexical Semantic Knowledge from Wikipedia and Wiktionary.. In: Proc. of the Sixth International Conference on Language Resources and Evaluation (LREC), Marrakech, Morocco, pp. 1646–1652. European Language Resources Association (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Andrea Giovanni Nuzzolese
    • 1
    • 2
  • Aldo Gangemi
    • 1
  • Valentina Presutti
    • 1
  • Paolo Ciancarini
    • 1
    • 2
  1. 1.STLab-ISTC Consiglio Nazionale delle RicercheRomeItaly
  2. 2.Dipartimento di Scienze dell’InformazioneUniversità di BolognaItaly

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