Word association norms, mutual information, and lexicography
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
Corpus-based and knowledge-based measures of text semantic similarity
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
DBpedia: a nucleus for a web of open data
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
NeMa: fast graph search with label similarity
Proceedings of the VLDB Endowment
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Although a formal query language, SPARQL, is available for accessing DBpedia, it remains challenging for users to query the knowledge unless they are familiar with the syntax of SPARQL and the underlying ontology. We have developed both an intuitive semantic graph notation or interface allowing one to pose a query by annotating a graph with natural language terms denoting entities and relations and a system that automatically translates the query into SPARQL to produce an answer. Our key contributions are the robust techniques, combining statistical association and semantic similarity, that map user terms to the most appropriate classes and properties used in the DBpedia Ontology.