Utilize este identificador para referenciar este registo: http://hdl.handle.net/10071/34199
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Campo DCValorIdioma
dc.contributor.authorDuwadi, S.-
dc.contributor.authorCoutinho, C.-
dc.contributor.editorNuno Mateus Coelho-
dc.contributor.editorManuela Cruz Cunha-
dc.date.accessioned2025-04-10T08:39:51Z-
dc.date.available2025-04-10T08:39:51Z-
dc.date.issued2024-
dc.identifier.citationDuwadi, S., & Coutinho, C. (2024). ChatGPT based recommendation system for retail shops. In N. M.-Coelho, & M. C. Cunha (Eds.), Procedia Computer Science (pp. 253-260). Elsevier. https://doi.org/10.1016/j.procs.2024.05.103-
dc.identifier.issn1877-0509-
dc.identifier.urihttp://hdl.handle.net/10071/34199-
dc.description.abstractThe rapid growth of e-commerce platforms has emphasized the significance of personalized recommendation systems in enhancing user engagement and satisfaction. This research paper presents the development and evaluation of an innovative Product Recommendation System that leverages advanced Artificial Intelligence (AI) techniques to provide tailored product suggestions. The primary objective is to create a user-centric experience by integrating an AI assistant, enabling natural and interactive interactions. Through a comprehensive survey conducted to understand customer behaviour while purchasing product using AI, the study aims to assess the system's effectiveness in delivering accurate recommendations and providing a seamless purchasing experience. The paper contributes to the field by showcasing the practical implementation of AI-driven recommendation systems, highlighting their potential to transform e-commerce interactions.eng
dc.language.isoeng-
dc.publisherElsevier-
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04466%2F2020/PT-
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F04466%2F2020/PT-
dc.relation.ispartofProcedia Computer Science-
dc.rightsopenAccess-
dc.subjectArtificial Intelligence (AI)eng
dc.subjectAI assistanteng
dc.subjectRetail businesseng
dc.subjectE-commerceeng
dc.subjectPersonalized recommendation systemseng
dc.subjectMachine learningeng
dc.subjectChatGPTeng
dc.titleChatGPT based recommendation system for retail shopseng
dc.typeconferenceObject-
dc.event.title2023 International Conference on Industry Sciences and Computer Science Innovation, iSCSi 2023-
dc.event.typeConferênciapt
dc.event.locationLisboaeng
dc.event.date2023-
dc.pagination253 - 260-
dc.peerreviewedyes-
dc.volume237-
dc.date.updated2025-04-10T09:38:57Z-
dc.description.versioninfo:eu-repo/semantics/publishedVersion-
dc.identifier.doi10.1016/j.procs.2024.05.103-
dc.subject.fosDomínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informaçãopor
dc.subject.fosDomínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informáticapor
iscte.subject.odsIndústria, inovação e infraestruturaspor
iscte.subject.odsCidades e comunidades sustentáveispor
iscte.subject.odsProdução e consumo sustentáveispor
iscte.identifier.cienciahttps://ciencia.iscte-iul.pt/id/ci-pub-103342-
iscte.alternateIdentifiers.scopus2-s2.0-85195382049-
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