Discovering Types in RDF Datasets

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9341)

Abstract

An increasing number of linked datasets is published on the Web, expressed in RDF(S)/OWL. Interlinking, matching or querying these datasets require some knowledge about the types and properties they contain. This work presents an approach, relying on a clustering algorithm, which provides the types describing a dataset when this information is incomplete or missing.

Keywords

Type extraction Clustering Semantic web Linked data 

References

  1. 1.
    Christodoulou, K., Paton, N.W., Fernandes, A.A.: Structure inference for linked data sources using clustering. In: EDBT/ICDT (2013)Google Scholar
  2. 2.
    Ester, M., Kriegel, H.-P., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: Kdd (1996)Google Scholar
  3. 3.
    Gangemi, A., Nuzzolese, A.G., Presutti, V., Draicchio, F., Musetti, A., Ciancarini, P.: Automatic typing of DBpedia entities. In: Cudré-Mauroux, P., Heflin, J., Sirin, E., Tudorache, T., Euzenat, J., Hauswirth, M., Parreira, J.X., Hendler, J., Schreiber, G., Bernstein, A., Blomqvist, E. (eds.) ISWC 2012, Part I. LNCS, vol. 7649, pp. 65–81. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  4. 4.
    Kellou-Menouer, K., Kedad, Z.: A clustering based approach for type discovery in RDF data sources. Revue des Nouvelles Technologies de l’Information, EGC (2015)Google Scholar
  5. 5.
    Kellou-Menouer, K., Kedad, Z.: Using clustering for type discovery in the semantic web. Fouille de Donnees Complexes (2015, to appear)Google Scholar
  6. 6.
    Nestorov, S., Abiteboul, S., Motwani, R.: Extracting schema from semistructured data. In: ACM SIGMOD Record (1998)Google Scholar
  7. 7.
    Nuzzolese, A.G., Gangemi, A., Presutti, V., Ciancarini, P.: Type inference through the analysis of Wikipedia links. In: LDOW (2012)Google Scholar
  8. 8.
    Paulheim, H., Bizer, C.: Type inference on noisy RDF data. In: Alani, H., Kagal, L., Fokoue, A., Groth, P., Biemann, C., Parreira, J.X., Aroyo, L., Noy, N., Welty, C., Janowicz, K. (eds.) ISWC 2013, Part I. LNCS, vol. 8218, pp. 510–525. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  9. 9.
    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
  10. 10.
    Wang, Q.Y., Yu, J.X., Wong, K.-F.: Approximate graph schema extraction for semi-structured data. In: Zaniolo, C., Grust, T., Scholl, M.H., Lockemann, P.C. (eds.) EDBT 2000. LNCS, vol. 1777, pp. 302–316. Springer, Heidelberg (2000) CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.PRISM - University of Versailles Saint-Quentin-en-YvelinesVersaillesFrance

Personalised recommendations