Leveraging transformer-based language models for enhanced service insight in tourism

dc.authorid0009-0008-5993-6336
dc.authorid0000-0003-3903-7356
dc.authorid0000-0001-5106-0044
dc.contributor.authorEr, Aleynaen_US
dc.contributor.authorÖzçelik, Şuayb Talhaen_US
dc.contributor.authorYöndem, Meltem Turhanen_US
dc.date.accessioned2024-02-20T17:13:07Z
dc.date.available2024-02-20T17:13:07Z
dc.date.issued2023-12-22
dc.departmentIşık Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering and Natural Sciences, Department of Computer Engineeringen_US
dc.description.abstractCustomer feedback is a valuable resource for enhancing customer experience and identifying areas that require improvement. Utilizing user insights allows a tourism company to identify and address problematic points in its service delivery, provide feedback to partner companies regarding their product offerings, and even reconsider agreements by incorporating these opinions when curating their product portfolio. Setur implemented a systematic approach to collecting customer feedback by distributing "after-stay surveys'' to its customers via email following the completion of the agency services provided. Guest answers to open-ended questions that gather opinions about travel experience are analyzed by four tasks: user intention for answering, the sentiment of the review, subjects touched upon, and whom it concerned. For these tasks, transformer-based natural language processing (NLP) models BERT, DistilBERT, RoBERTa, and Electra are fine-Tuned to classify customer reviews. Based on the test results, it is observed that best practices could be gathered using Bert. In addition, we showed that different insights can be obtained from text comments made for two hotels in Aydin, Turkiye. Some users made complaints using neutral sentences. In some cases, people gave high scores to the numerical rating questions, but their open-ended questions could have a negative meaning.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationEr, A. & Özçelik, Ş. T. (2023). Leveraging transformer-based language models for enhanced service insight in tourism. Paper presented at the 4th International Informatics and Software Engineering Conference (IISEC), 1-6. doi:10.1109/IISEC59749.2023.10391041en_US
dc.identifier.doi10.1109/IISEC59749.2023.10391041
dc.identifier.endpage6
dc.identifier.isbn9798350318036
dc.identifier.isbn9798350318043
dc.identifier.scopus2-s2.0-85184654784
dc.identifier.scopusqualityN/A
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/11729/5904
dc.identifier.urihttp://dx.doi.org/10.1109/IISEC59749.2023.10391041
dc.indekslendigikaynakScopusen_US
dc.institutionauthorÖzçelik, Şuayb Talhaen_US
dc.institutionauthorid0000-0003-3903-7356
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherIEEEen_US
dc.relation.ispartof4th International Informatics and Software Engineering Conference (IISEC)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - İdari Personel ve Öğrencien_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBERTen_US
dc.subjectDistilBERTen_US
dc.subjectElectraen_US
dc.subjectRoBERTaen_US
dc.subjectTourismen_US
dc.subjectNatural language processing systemsen_US
dc.subjectCustomer experienceen_US
dc.subjectCustomer feedbacken_US
dc.subjectITS Servicesen_US
dc.subjectLanguage modelen_US
dc.subjectOpen-ended questionsen_US
dc.subjectService deliveryen_US
dc.titleLeveraging transformer-based language models for enhanced service insight in tourismen_US
dc.typeConference Objecten_US

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