Deep Learning Based Chatbot Adapted to the Electronic Funds Transfer Process of Turkish Banking

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dc.contributor.authorToprak, Ahmet
dc.contributor.authorTuran, Metin
dc.contributor.authorToprak, Feyzanur Sağlam
dc.date.accessioned2023-11-08T07:09:41Z
dc.date.available2023-11-08T07:09:41Z
dc.date.issued2023en_US
dc.departmentEnstitüler, Fen Bilimleri Enstitüsü, Bilgisayar Mühendisliği Ana Bilim Dalıen_US
dc.description.abstractAdvanced applications of Natural Language Processing require understanding the semantic of the language. If traditional machine learning techniques are used, the models built for conversations, called chatbots, are unable to be truly generic. On the other hand, deep learning allows us to extract the complexities within language and makes it easier to model. It can also leverage for building a chatbot which has a real conversation with human. In the study, Electronic Funds Transfer process of Turkish bank operations has been designed. A dictionary of terms used in this process has been created in order to train dialog model. Language descriptor layer first checks the language of command. Named Entity Recognition layer later, classifies the words according to their asset structures, especially the amount and account number information in the Electronic Funds Transfer process. LSTM architecture is used to keep the other stages of the dialog, so that order of dialog is in control. The performance evaluation of the designed model was calculated separately for 3 different EFT processes. According to the results obtained, a success rate of 70% was achieved in EFT with account number, 90% in EFT with IBAN number, and 90% in EFT with credit card number.en_US
dc.identifier.endpage362en_US
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85160418161en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage356en_US
dc.identifier.urihttps://hdl.handle.net/11467/6933
dc.identifier.volume11en_US
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherIsmail Saritasen_US
dc.relation.ispartofInternational Journal of Intelligent Systems and Applications in Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - İdari Personel ve Öğrencien_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjecthatbot system; intent classification; long short term memory; natural language processing; recurrent neural networksen_US
dc.titleDeep Learning Based Chatbot Adapted to the Electronic Funds Transfer Process of Turkish Bankingen_US
dc.typeArticleen_US

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