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Poster Papers

Track: Search

Paper Title:
How NAGA Uncoils: Searching with Entities and Relations

Authors:

  • Gjergji Kasneci (Max-Planck-Institute)
  • Fabian M. Suchanek (Max-Planck-Institute)
  • Maya Ramanath (Max-Planck-Institute)
  • Gerhard Weikum (Max-Planck-Institute)

Abstract:
Current keyword-oriented search engines for the World Wide Web do not allow specifying the semantics of queries. We address this limitation with NAGA, a new semantic search engine. NAGA builds on a large semantic knowledge base of binary relationships (facts) derived from the Web. NAGA provides a simple, yet expressive query language to query this knowledge base. The results are then ranked with an intuitive scoring mechanism. We show the effectiveness and utility of NAGA by comparing its output with that of Google on some interesting queries.

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