RehabRobo-Query: Answering Natural Language Queries about Rehabilitation Robotics Ontology on the Cloud

Tracking #: 1661-2873

This paper is currently under review
Authors: 
Zeynep Dogmus
Esra Erdem
Volkan Patoglu

Responsible editor: 
Guest Editors ENLI4SW 2016

Submission type: 
Full Paper
Abstract: 
We introduce a novel method to answer natural language queries about rehabilitation robotics, over the formal ontology RehabRobo-Onto. For that, (i) we design and develop a novel controlled natural language for rehabilitation robotics, called RehabRobo-CNL; (ii) we introduce translations of queries in RehabRobo-CNL into SPARQL queries, utilizing a novel concept of query description trees and description logics concepts; (iii) we use an automated reasoner to find answers to SPARQL queries. To facilitate the use of our method by experts, we develop an intelligent, interactive query answering system, called RehabRobo-Query, using Semantic Web technologies, and make it available on the cloud via Amazon web services. RehabRobo-Query guides the users to express their queries in natural language and displays the answers to queries in a readable format, possibly with links to detailed information. Easy access to information on RehabRobo-Onto through complex queries in natural language may help engineers inspire new rehabilitation robot designs, while also guiding practitioners to make more informed decisions on technology based rehabilitation.
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