skip to main content
10.1145/1963192.1963296acmotherconferencesArticle/Chapter ViewAbstractPublication PageswwwConference Proceedingsconference-collections
demonstration

YAGO2: exploring and querying world knowledge in time, space, context, and many languages

Published:28 March 2011Publication History

ABSTRACT

We present YAGO2, an extension of the YAGO knowledge base with focus on temporal and spatial knowledge. It is automatically built from Wikipedia, GeoNames, and WordNet, and contains nearly 10 million entities and events, as well as 80 million facts representing general world knowledge. An enhanced data representation introduces time and location as first-class citizens. The wealth of spatio-temporal information in YAGO can be explored either graphically or through a special time- and space-aware query language.

References

  1. S. Auer, C. Bizer, G. Kobilarov, J. Lehmann, R. Cyganiak, and Z. Ives. DBpedia: A Nucleus for a Web of Open Data. In ISWC ASWC, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. M. Banko, M. J. Cafarella, S. Soderland, M. Broadhead, and O. Etzioni. Open Information Extraction from the Web. In IJCAI, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. G. de Melo and G. Weikum. Towards a Universal Wordnet by Learning from Combined Evidence. In CIKM, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. F. Giunchiglia, V. Maltese, F. Farazi, and B. Dutta. GeoWordNet: A Resource for Geo-spatial Applications. In ESWC, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. C. Gutierrez, C. A. Hurtado, and A. Vaisman. Introducing Time into RDF. IEEE TKDE, 19:207--218, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. J. Hoffart, F. M. Suchanek, K. Berberich, and G. Weikum. YAGO2: A Spatially and Temporally Enhanced Knowledge Base from Wikipedia. Research report, Max-Planck-Institut für Informatik, 2010.Google ScholarGoogle Scholar
  7. M. Koubarakis and K. Kyzirakos. Modeling and Querying Metadata in the Semantic Sensor Web: The Model stRDF and the Query Language stSPARQL. In The Semantic Web: Research and Applications. 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. S. P. Ponzetto and M. Strube. Deriving a Large-Scale Taxonomy from Wikipedia. In AAAI, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. F. M. Suchanek, G. Kasneci, and G. Weikum. YAGO: A Core of Semantic Knowledge. In WWW, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. O. Udrea, D. Reforgiato, and V. Subrahmanian. Annotated RDF. ACM Tr. Comp. Log., 11(2), 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. YAGO2: exploring and querying world knowledge in time, space, context, and many languages

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Other conferences
        WWW '11: Proceedings of the 20th international conference companion on World wide web
        March 2011
        552 pages
        ISBN:9781450306379
        DOI:10.1145/1963192

        Copyright © 2011 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 28 March 2011

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • demonstration

        Acceptance Rates

        Overall Acceptance Rate1,899of8,196submissions,23%

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader