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

Tracking #: 1808-3021

Zeynep Dogmus
Esra Erdem
Volkan Patoglu

Responsible editor: 
Guest Editors ENLI4SW 2016

Submission type: 
Full Paper
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; (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.
Full PDF Version: 


Solicited Reviews:
Click to Expand/Collapse
Review #1
Anonymous submitted on 16/May/2018
Review Comment:

The authors have addressed all comments suggested by the reviewers.

Regarding the first comment of the first reviewer about the need to justify why the ontology was built from scratch instead of (partially) reusing well-known ontologies, the authors had included an explanation in the previous revision. For the completeness of the justification, the authors could provide in the final version 1-2 examples of conceptual mappings (1-2 sentences in Section 2) that can be defined between the References and Owners concepts of their model, and FOAF, BIBO or FaBio. I think this would further strengthen their explanation.