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Abstract:
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 user interface, enter queries in NAGA's query language
and tune the ranking parameters to test various ranking aspects.
