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dc.contributor.authorRobin, Cécile
dc.contributor.authorIsazad Mashinchi, Mona
dc.contributor.authorAhmadi Zeleti, Fatemeh
dc.contributor.authorOjo, Adegboyega
dc.contributor.authorBuitelaar, Paul
dc.date.accessioned2020-05-18T11:30:01Z
dc.date.available2020-05-18T11:30:01Z
dc.date.issued2020-05
dc.identifier.citationRobin, Cécile, Isazad Mashinchi, Mona, Ahmadi Zeleti, Fatemeh, Ojo, Adegboyega, & Buitelaar, Paul. (2020). A term extraction approach to survey analysis in health care. Paper for the 12th Language Resources and Evaluation Conference (LREC), Marseille, France, 11-16 May.en_IE
dc.identifier.urihttp://hdl.handle.net/10379/15975
dc.description.abstractThe voice of the customer has for a long time been a key focus of businesses in all domains. It has received a lot of attention from the research community in Natural Language Processing (NLP) resulting in many approaches to analyzing customers feedback ((aspect-based) sentiment analysis, topic modeling, etc.). In the health domain, public and private bodies are increasingly prioritizing patient engagement for assessing the quality of the service given at each stage of the care. Patient and customer satisfaction analysis relate in many ways. In the domain of health particularly, a more precise and insightful analysis is needed to help practitioners locate potential issues and plan actions accordingly. We introduce here an approach to patient experience with the analysis of free text questions from the 2017 Irish National Inpatient Survey campaign using term extraction as a means to highlight important and insightful subject matters raised by patients. We evaluate the results by mapping them to a manually constructed framework following the Activity, Resource, Context (ARC) methodology (Ordenes, 2014) and specific to the health care environment, and compare our results against manual annotations done on the full 2017 dataset based on those categories.en_IE
dc.description.sponsorshipThis work presented in this paper was partially supported by the Patient Centred Service Improvement (PaCSI Project) and by Science Foundation Ireland grant 12/RC/2289 2 (Insight).en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherEuropean Language Resources Associationen_IE
dc.relation.ispartofThe 12th Language Resources and Evaluation Conference LRECen
dc.subjecthealth careen_IE
dc.subjectnatural language processingen_IE
dc.subjectARC frameworken_IE
dc.subjectpatient engagementen_IE
dc.subjectevaluation methodologyen_IE
dc.subjectpatient experienceen_IE
dc.subjectterm extractionen_IE
dc.titleA term extraction approach to survey analysis in health careen_IE
dc.typeConference Paperen_IE
dc.date.updated2020-05-15T16:14:16Z
dc.local.publishedsourcehttp://www.lrec-conf.org/proceedings/lrec2020/index.htmlen_IE
dc.description.peer-reviewedpeer-reviewed
dc.contributor.funderScience Foundation Irelanden_IE
dc.internal.rssid21039755
dc.local.contactCécile Robin, -. - Email: cecile.c.robin@nuigalway.ie
dc.local.copyrightcheckedYes
dc.local.versionPUBLISHED
dcterms.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/en_IE
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