4 May 2017 In-context query reformulation for failing SPARQL queries
Author Affiliations +
Abstract
Knowledge bases for decision support systems are growing increasingly complex, through continued advances in data ingest and management approaches. However, humans do not possess the cognitive capabilities to retain a bird’s-eyeview of such knowledge bases, and may end up issuing unsatisfiable queries to such systems. This work focuses on the implementation of a query reformulation approach for graph-based knowledge bases, specifically designed to support the Resource Description Framework (RDF). The reformulation approach presented is instance-and schema-aware. Thus, in contrast to relaxation techniques found in the state-of-the-art, the presented approach produces in-context query reformulation.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Amar Viswanathan, Amar Viswanathan, James R. Michaelis, James R. Michaelis, Taylor Cassidy, Taylor Cassidy, Geeth de Mel, Geeth de Mel, James Hendler, James Hendler, } "In-context query reformulation for failing SPARQL queries", Proc. SPIE 10190, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VIII, 101900M (4 May 2017); doi: 10.1117/12.2266590; https://doi.org/10.1117/12.2266590
PROCEEDINGS
8 PAGES


SHARE
Back to Top