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SIGMOD
2008
ACM

NAGA: harvesting, searching and ranking knowledge

11 years 11 months ago
NAGA: harvesting, searching and ranking knowledge
The presence of encyclopedic Web sources, such as Wikipedia, the Internet Movie Database (IMDB), World Factbook, etc. calls for new querying techniques that are simple and yet more expressive than those provided by standard keyword-based search engines. Searching for explicit knowledge needs to consider inherent semantic structures involving entities and relationships. In this demonstration proposal, we describe a semantic search system named NAGA. NAGA operates on a knowledge graph, which contains millions of entities and relationships derived from various encyclopedic Web sources, such as the ones above. NAGA's graph-based query language is geared towards expressing queries with additional semantic information. Its scoring model is based on the principles of generative language models, and formalizes several desiderata such as confidence, informativeness and compactness of answers. We propose a demonstration of NAGA which will allow users to browse the knowledge base through a ...
Gjergji Kasneci, Fabian M. Suchanek, Georgiana Ifr
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where SIGMOD
Authors Gjergji Kasneci, Fabian M. Suchanek, Georgiana Ifrim, Shady Elbassuoni, Maya Ramanath, Gerhard Weikum
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