Natural language interfaces to conceptual models

Accessing structured data in the form of ontologies currently requires the use of formal query languages (e.g., SeRQL or SPARQL) which pose significant difficulties for non-expert users. One way to lower the learning overhead and make ontology queries more straightforward is through a Natural Lan- g...

Full description

Bibliographic Details
Main Author: Damljanovic, Danica
Other Authors: Cunningham, Hamish
Published: University of Sheffield 2011
Subjects:
Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.548473
id ndltd-bl.uk-oai-ethos.bl.uk-548473
record_format oai_dc
spelling ndltd-bl.uk-oai-ethos.bl.uk-5484732017-10-04T03:25:48ZNatural language interfaces to conceptual modelsDamljanovic, DanicaCunningham, Hamish2011Accessing structured data in the form of ontologies currently requires the use of formal query languages (e.g., SeRQL or SPARQL) which pose significant difficulties for non-expert users. One way to lower the learning overhead and make ontology queries more straightforward is through a Natural Lan- guage Interface (NLI). While there are existing NLIs to structured data with reasonable performance, they tend to require expensive customisation to each new domain. Additionally, they often require specific adherence to a pre-defined syntax which, in turn, means that users still have to undergo training. In this thesis, we study the usability of NLIs from two perspectives: that of the developer who is customising the NLI system, and that of the end-user who uses it for querying. We investigate whether usability methods such as feedback and clarification dialogs can increase the usability for end users and reduce the customisation effort for the developers. To that end, we have developed two systems, QuestIO and FREyA, whose design, evaluation and comparison with similar systems form the core of the contribution of this thesis.006.3University of Sheffieldhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.548473http://etheses.whiterose.ac.uk/1630/Electronic Thesis or Dissertation
collection NDLTD
sources NDLTD
topic 006.3
spellingShingle 006.3
Damljanovic, Danica
Natural language interfaces to conceptual models
description Accessing structured data in the form of ontologies currently requires the use of formal query languages (e.g., SeRQL or SPARQL) which pose significant difficulties for non-expert users. One way to lower the learning overhead and make ontology queries more straightforward is through a Natural Lan- guage Interface (NLI). While there are existing NLIs to structured data with reasonable performance, they tend to require expensive customisation to each new domain. Additionally, they often require specific adherence to a pre-defined syntax which, in turn, means that users still have to undergo training. In this thesis, we study the usability of NLIs from two perspectives: that of the developer who is customising the NLI system, and that of the end-user who uses it for querying. We investigate whether usability methods such as feedback and clarification dialogs can increase the usability for end users and reduce the customisation effort for the developers. To that end, we have developed two systems, QuestIO and FREyA, whose design, evaluation and comparison with similar systems form the core of the contribution of this thesis.
author2 Cunningham, Hamish
author_facet Cunningham, Hamish
Damljanovic, Danica
author Damljanovic, Danica
author_sort Damljanovic, Danica
title Natural language interfaces to conceptual models
title_short Natural language interfaces to conceptual models
title_full Natural language interfaces to conceptual models
title_fullStr Natural language interfaces to conceptual models
title_full_unstemmed Natural language interfaces to conceptual models
title_sort natural language interfaces to conceptual models
publisher University of Sheffield
publishDate 2011
url http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.548473
work_keys_str_mv AT damljanovicdanica naturallanguageinterfacestoconceptualmodels
_version_ 1718543458259435520