Keyword Searching and Browsing in Databases using BANKS
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Proceedings of the 16th international conference on World Wide Web
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
SPARQ2L: towards support for subgraph extraction queries in rdf databases
Proceedings of the 16th international conference on World Wide Web
NAGA: Searching and Ranking Knowledge
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Learning to create data-integrating queries
Proceedings of the VLDB Endowment
Hermes: a travel through semantics on the data web
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Classifying Web Pages by Using Knowledge Bases for Entity Retrieval
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
Enabling information extraction by inference of regular expressions from sample entities
Proceedings of the 20th ACM international conference on Information and knowledge management
Searching web data: An entity retrieval and high-performance indexing model
Web Semantics: Science, Services and Agents on the World Wide Web
A novel metric for information retrieval in semantic networks
ESWC'11 Proceedings of the 8th international conference on The Semantic Web
Compressed data structures for annotated web search
Proceedings of the 21st international conference on World Wide Web
Expressive languages for selecting groups from graph-structured data
Proceedings of the 22nd international conference on World Wide Web
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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.