Application of ChatGPT in the tourism domain: potential structures and challenges

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dc.authorid0000-0003-3903-7356
dc.authorid0000-0001-5106-0044
dc.contributor.authorKılıçlıoğlu, Orkun Mehmeten_US
dc.contributor.authorÖzçelik, Şuayb Talhaen_US
dc.contributor.authorYöndem, Meltem Turhanen_US
dc.date.accessioned2024-02-20T16:30:20Z
dc.date.available2024-02-20T16:30:20Z
dc.date.issued2023-12-23
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.abstractThe tourism industry stands out as a sector where effective customer communication significantly influences sales and customer satisfaction. The recent shift from traditional natural language processing methodologies to state-of-The-Art deep learning and transformer-based models has revolutionized the development of Conversational AI tools. These tools can provide comprehensive information about a company's product portfolio, enhancing customer engagement and decision-making. One potential Conversational AI application can be developed with ChatGPT. In this study, we explore the potential of using ChatGPT, a cutting-edge Conversational AI, in the context of Setur's products and services, focusing on two distinct scenarios: intention recognition and response generation. We incorporate Setur-specific data, including hotel information and annual catalogs. Our research aims to present potential structures and strategies for utilizing Language Model-based systems, particularly ChatGPT, in the tourism domain. We investigate the advantages and disadvantages of three different architectures and evaluate whether a restrictive or more independent model would be suitable for our application. Despite the impressive performance of Large Language Models (LLMs) in generating human-like dialogues, their end-To-end application faces limitations, such as system prompt constraints, fine-Tuning challenges, and model unavailability. Moreover, semantic search fails to deliver satisfactory performance when searching filters that require clear answers. To address these issues, we propose a hybrid approach that employs external interventions, the assignment of different GPT agents according to intent analysis, and traditional methods at specific junctures, which will facilitate the integration of domain knowledge into these systems.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationKılıçlıoğlu, O. M., Özçelik, Ş. T. & Yöndem, M. T. (2023). Application of ChatGPT in the tourism domain: potential structures and challenges. Paper presented at the 4th International Informatics and Software Engineering Conference (IISEC), 1-4. doi:10.1109/IISEC59749.2023.10390989en_US
dc.identifier.doi10.1109/IISEC59749.2023.10390989
dc.identifier.endpage4
dc.identifier.isbn9798350318036
dc.identifier.isbn9798350318043
dc.identifier.scopus2-s2.0-85184656123
dc.identifier.scopusqualityN/A
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/11729/5902
dc.identifier.urihttp://dx.doi.org/10.1109/IISEC59749.2023.10390989
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.subjectChatGPTen_US
dc.subjectLarge language modelsen_US
dc.subjectTourismen_US
dc.subjectTravel assistanten_US
dc.subjectComputational linguisticsen_US
dc.subjectCustomer satisfactionen_US
dc.subjectDeep learningen_US
dc.subjectDomain knowledgeen_US
dc.subjectNatural language processing systemsen_US
dc.subjectSalesen_US
dc.subjectSemanticsen_US
dc.subjectSemantic searchen_US
dc.subjectTourism industryen_US
dc.subjectFocusingen_US
dc.subjectChatbotsen_US
dc.subjectTransformersen_US
dc.subjectArtificial intelligenceen_US
dc.subjectInformaticsen_US
dc.subjectTourism domainen_US
dc.subjectLanguage modelen_US
dc.subjectKnowledge integrationen_US
dc.subjectRecent shiften_US
dc.subjectSpecial occasionsen_US
dc.subjectEnd-usersen_US
dc.subjectKalman filteren_US
dc.subjectAPI callsen_US
dc.subjectSales representativesen_US
dc.titleApplication of ChatGPT in the tourism domain: potential structures and challengesen_US
dc.typeConference Objecten_US

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