Zhishi.me - Weaving Chinese Linking Open Data

  • Xing Niu
  • Xinruo Sun
  • Haofen Wang
  • Shu Rong
  • Guilin Qi
  • Yong Yu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7032)

Abstract

Linking Open Data (LOD) has become one of the most important community efforts to publish high-quality interconnected semantic data. Such data has been widely used in many applications to provide intelligent services like entity search, personalized recommendation and so on. While DBpedia, one of the LOD core data sources, contains resources described in multilingual versions and semantic data in English is proliferating, there is very few work on publishing Chinese semantic data. In this paper, we present Zhishi.me, the first effort to publish large scale Chinese semantic data and link them together as a Chinese LOD (CLOD). More precisely, we identify important structural features in three largest Chinese encyclopedia sites (i.e., Baidu Baike, Hudong Baike, and Chinese Wikipedia) for extraction and propose several data-level mapping strategies for automatic link discovery. As a result, the CLOD has more than 5 million distinct entities and we simply link CLOD with the existing LOD based on the multilingual characteristic of Wikipedia. Finally, we also introduce three Web access entries namely SPARQL endpoint, lookup interface and detailed data view, which conform to the principles of publishing data sources to LOD.

Keywords

Link Data Semantic Data Internal Link External Link Link Open Data 
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.

References

  1. 1.
    Auer, S., Lehmann, J.: What Have Innsbruck and Leipzig in Common? Extracting Semantics from Wiki Content. In: Franconi, E., Kifer, M., May, W. (eds.) ESWC 2007. LNCS, vol. 4519, pp. 503–517. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  2. 2.
    Berrueta, D., Phipps, J.: Best Practice Recipes for Publishing RDF Vocabularies. W3C Working Group Note (August 2008), http://www.w3.org/TR/2008/NOTE-swbp-vocab-pub-20080828/
  3. 3.
    Bizer, C., Heath, T., Berners-Lee, T.: Linked Data - The Story So Far. Int. J. Semantic Web Inf. Syst. 5(3), 1–22 (2009)CrossRefGoogle Scholar
  4. 4.
    Bizer, C., Lehmann, J., Kobilarov, G., Auer, S., Becker, C., Cyganiak, R., Hellmann, S.: DBpedia - A crystallization point for the Web of Data. J. Web Sem. 7(3), 154–165 (2009)CrossRefGoogle Scholar
  5. 5.
    Dean, J., Ghemawat, S.: MapReduce: Simplified Data Processing on Large Clusters. In: OSDI, pp. 137–150 (2004)Google Scholar
  6. 6.
    Duerst, M., Suignard, M.: Internationalized Resource Identifiers (IRIs). proposed standard 3987 (January 2005)Google Scholar
  7. 7.
    Fu, B., Brennan, R., O’Sullivan, D.: Cross-Lingual Ontology Mapping – An Investigation of the Impact of Machine Translation. In: Gómez-Pérez, A., Yu, Y., Ding, Y. (eds.) ASWC 2009. LNCS, vol. 5926, pp. 1–15. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  8. 8.
    Hogan, A., Harth, A., Passant, A., Decker, S., Polleres, A.: Weaving the pedantic web. In: 3rd International Workshop on Linked Data on the Web, LDOW 2010 (2010)Google Scholar
  9. 9.
    Jain, P., Hitzler, P., Sheth, A.P., Verma, K., Yeh, P.Z.: Ontology Alignment for Linked Open Data. In: Patel-Schneider, et al. (eds.) [15], pp. 402–417Google Scholar
  10. 10.
    Levenshtein, V.: Binary codes capable of correcting deletions, insertions, and reversals. Soviet Physics Doklady 10(8), 707–710 (1966)MATHGoogle Scholar
  11. 11.
    de Melo, G., Weikum, G.: Towards a universal wordnet by learning from combined evidence. In: Cheung, D.W.L., Song, I.Y., Chu, W.W., Hu, X., Lin, J.J. (eds.) CIKM, pp. 513–522. ACM (2009)Google Scholar
  12. 12.
    Ngai, G., Carpuat, M., Fung, P.: Identifying Concepts Across Languages: A First Step towards a Corpus-based Approach to Automatic Ontology Alignment. In: COLING (2002)Google Scholar
  13. 13.
    Nikolov, A., Uren, V.S., Motta, E., De Roeck, A.: Integration of Semantically Annotated Data by the KnoFuss Architecture. In: Gangemi, A., Euzenat, J. (eds.) EKAW 2008. LNCS (LNAI), vol. 5268, pp. 265–274. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  14. 14.
    Parundekar, R., Knoblock, C.A., Ambite, J.L.: Linking and building ontologies of linked data. In: Patel-Schneider, et al. (eds.) [15], pp. 598–614Google Scholar
  15. 15.
    Patel-Schneider, P.F., Pan, Y., Hitzler, P., Mika, P., Zhang, L., Pan, J.Z., Horrocks, I., Glimm, B. (eds.): ISWC 2010, Part I. LNCS, vol. 6496. Springer, Heidelberg (2010)Google Scholar
  16. 16.
    Raggett, D., Hors, A.L., Jacobs, I.: HTML 4.01 Specification - Appendix B: Performance, Implementation, and Design Notes. W3C Recommendation (December 1999), http://www.w3.org/TR/html4/appendix/notes.html
  17. 17.
    Raimond, Y., Sutton, C., Sandler, M.: Automatic interlinking of music datasets on the semantic web. In: Proceedings of the 1st Workshop about Linked Data on the Web, LDOW 2008 (2008)Google Scholar
  18. 18.
    Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: a core of semantic knowledge. In: Williamson, C.L., Zurko, M.E., Patel-Schneider, P.F., Shenoy, P.J. (eds.) WWW, pp. 697–706. ACM (2007)Google Scholar
  19. 19.
    Volz, J., Bizer, C., Gaedke, M., Kobilarov, G.: Discovering and Maintaining Links on the Web of Data. In: Bernstein, A., Karger, D.R., Heath, T., Feigenbaum, L., Maynard, D., Motta, E., Thirunarayan, K. (eds.) ISWC 2009. LNCS, vol. 5823, pp. 650–665. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  20. 20.
    Zhao, J.: Publishing Chinese medicine knowledge as Linked Data on the Web. Chinese Medicine 5(1), 1–12 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Xing Niu
    • 1
  • Xinruo Sun
    • 1
  • Haofen Wang
    • 1
  • Shu Rong
    • 1
  • Guilin Qi
    • 2
  • Yong Yu
    • 1
  1. 1.APEX Data & Knowledge Management LabShanghai Jiao Tong UniversityChina
  2. 2.Southeast UniversityChina

Personalised recommendations