Poster Title:

How Naga Uncoils: Searching with Entities and Relations

Authors:

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

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.