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dc.contributor.authorRanasinghe, Tharindu
dc.contributor.authorSaadany, Hadeel
dc.contributor.authorPlum, Alistair
dc.contributor.authorMandhari, Salim
dc.contributor.authorMohamed, Emad
dc.contributor.authorOrasan, Constantin
dc.contributor.authorMitkov, Ruslan
dc.date.accessioned2019-10-11T11:40:03Z
dc.date.available2019-10-11T11:40:03Z
dc.date.issued2019-12-12
dc.identifier.citationRanasinghe, T. et al.(2019) RGCL at IDAT: deep learning models for irony detection in Arabic language, in Metha, P., Rosso, P., Majumder, P. and Mitra, M. (eds.) Working Notes of FIRE 2019 - Forum for Information Retrieval Evaluation, Kolkata, India, 12th-15th December, 2019. CEUR Workshop Proceedings Volume 2517, 2019, Pages 416-425.en
dc.identifier.issn1613-0073
dc.identifier.urihttp://hdl.handle.net/2436/622828
dc.description.abstractThis article describes the system submitted by the RGCL team to the IDAT 2019 Shared Task: Irony Detection in Arabic Tweets. The system detects irony in Arabic tweets using deep learning. The paper evaluates the performance of several deep learning models, as well as how text cleaning and text pre-processing influence the accuracy of the system. Several runs were submitted. The highest F1 score achieved for one of the submissions was 0.818 making the team RGCL rank 4th out of 10 teams in final results. Overall, we present a system that uses minimal pre-processing but capable of achieving competitive results.en
dc.formatapplication/PDFen
dc.language.isoenen
dc.publisherIDATen
dc.relation.urlhttp://irlab.daiict.ac.in/~Parth/T4-5.pdfen
dc.subjectComputational linguisticsen
dc.subjectIrony Detectionen
dc.titleRGCL at IDAT: deep learning models for irony detection in Arabic languageen
dc.typeConference contributionen
dc.date.updated2019-09-27T11:28:35Z
dc.conference.nameIrony Detection in Arabic Tweets (IDAT 2019) Shared Task
dc.conference.locationKolkata, India
pubs.finish-date2019-12-15
pubs.start-date2019-12-12
dc.date.accepted2019-09-16
rioxxterms.funderUniversity of Wolverhamptonen
rioxxterms.identifier.projectUOW11102019COen
rioxxterms.versionAMen
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0/en
rioxxterms.licenseref.startdate2019-12-12en
dc.source.volume2517
dc.source.beginpage416
dc.source.endpage425
refterms.dateFCD2019-10-11T11:38:40Z
refterms.versionFCDAM


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