Proceedings of the Semantic Web Evaluation Challenge, ESWC

UMBC_Ebiquity-SFQ: Schema Free Querying System

Zareen Syed, Lushan Han, Muhammad Mahbubur Rahman, Tim Finin, James Kukla, and Jeehye Yun

June 1, 2015

Users need better ways to explore large complex linked data resources. Using SPARQL requires not only mastering its syntax and semantics but also understanding the RDF data model, the ontology and URIs for entities of interest. Natural language question answering systems solve the problem, but these are still subjects of research. The Schema agnostic SPARQL queries task defined in SAQ-2015 challenge consists of schema-agnostic queries following the syntax of the SPARQL standard, where the syntax and semantics of operators are maintained, while users are free to choose words, phrases and entity names irrespective of the underlying schema or ontology. This combination of query skeleton with keywords helps to remove some of the ambiguity. We describe our framework for handling schema agnostic or schema free queries and discuss enhancements to handle the SAQ-2015 challenge queries. The key contributions are the robust methods that combine statistical association and semantic similarity to map user terms to the most appropriate classes and properties used in the underlying ontology and type inference for user input concepts based on concept linking.

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Type: InProceedings

Publisher: Springer

Series: Communications in Computer and Information Science

Volume: 548

Note: (2015 ESWC Schema Agnostic Query Challenge Award)

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