Gotowa bibliografia na temat „Chatbot dialog”
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Artykuły w czasopismach na temat "Chatbot dialog"
Le, Nhat, A. B. Siddique, Fuad Jamour, Samet Oymak i Vagelis Hristidis. "Generating Predictable and Adaptive Dialog Policies in Single- and Multi-domain Goal-oriented Dialog Systems". International Journal of Semantic Computing 15, nr 04 (grudzień 2021): 419–39. http://dx.doi.org/10.1142/s1793351x21400109.
Pełny tekst źródłaFang, Jiyang. "Analysis on Chatbot Performance based on Attention Mechanism". Highlights in Science, Engineering and Technology 39 (1.04.2023): 151–56. http://dx.doi.org/10.54097/hset.v39i.6517.
Pełny tekst źródłaSuh, Jeehae. "A Study on the Conformity of Chatbot Builder as a Korean Speech Practice Tool". Korean Society of Culture and Convergence 45, nr 1 (31.01.2023): 61–70. http://dx.doi.org/10.33645/cnc.2023.01.45.01.61.
Pełny tekst źródłaDehankar, Archana, Shyamal Kirpan, Abhayraj Jha, Gitesh Thosare, Adarsh Bhaisare i Sumit Mankar. "AI CHATBOT USING DIALOG FLOW". International Journal of Computer Science and Mobile Computing 11, nr 5 (30.05.2022): 68–74. http://dx.doi.org/10.47760/ijcsmc.2022.v11i05.006.
Pełny tekst źródłaDehankar, Archana, Shyamal Kirpan, Abhayraj Jha, Gitesh Thosare, Adarsh Bhaisare i Sumit Mankar. "AI CHATBOT USING DIALOG FLOW". International Journal of Computer Science and Mobile Computing 11, nr 5 (30.05.2022): 68–74. http://dx.doi.org/10.47760/ijcsmc.2022.v11i05.006.
Pełny tekst źródłaZand, Aria, Arjun Sharma, Zack Stokes, Courtney Reynolds, Alberto Montilla, Jenny Sauk i Daniel Hommes. "An Exploration Into the Use of a Chatbot for Patients With Inflammatory Bowel Diseases: Retrospective Cohort Study". Journal of Medical Internet Research 22, nr 5 (26.05.2020): e15589. http://dx.doi.org/10.2196/15589.
Pełny tekst źródłaBogdanova, A. N., i G. A. Fedorova. "Chatbots as a component of the content of teaching the basics of artificial intelligence at school". Informatics in school, nr 2 (17.07.2022): 39–45. http://dx.doi.org/10.32517/2221-1993-2022-21-2-39-45.
Pełny tekst źródłaChen, Jenhui, Obinna Agbodike i Lei Wang. "Memory-Based Deep Neural Attention (mDNA) for Cognitive Multi-Turn Response Retrieval in Task-Oriented Chatbots". Applied Sciences 10, nr 17 (22.08.2020): 5819. http://dx.doi.org/10.3390/app10175819.
Pełny tekst źródłaWang, Youwei. "Discover two Neural Machine Translation model variables' effects on Chatbot's performance". Highlights in Science, Engineering and Technology 41 (30.03.2023): 17–22. http://dx.doi.org/10.54097/hset.v41i.6737.
Pełny tekst źródłaReddy, Mr P. Rajashekar. "Enhancing User Experience: A Study on Dialogflow Chatbot Implementation". INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, nr 03 (7.03.2024): 1–11. http://dx.doi.org/10.55041/ijsrem29070.
Pełny tekst źródłaRozprawy doktorskie na temat "Chatbot dialog"
Kero, Chanelle, i Veronica Törnblom. "Utveckling av en chatbots dialog för implementation i en webbaserad kundtjänst". Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-69046.
Pełny tekst źródłaAutomation of customer service through implementation of chatbots is becoming increasingly common in order to provide customers with a more accessible and efficient service. When implementing chatbots in customer services, human control and the customer experience are partially shifted to a digital system, which puts requirement on the chatbot’s dialogue. The purpose of this report is to develop an artifact for a client. The artifact is a web page containing a chatbot. The report aims to develop design principles for development of chatbots and their dialogues in a customer service. The research method used in the development of the artifact was Design Science Research Methodology (DSRM). A literature study was conducted, and data was collected through meetings and an interview with the client. The report resulted in a demo page containing a chatbot and a page for administrators with an overview of saved chats. Three design principles were also formulated for developing chatbots in customer service, which is the contribution of the report. The conclusions identified were that a chatbot should check that the user got the correct answer, a chatbot should offer human service in case of misunderstanding, a chatbot cannot fully replace human service and a chatbot should have a structured data collection of completed interactions for developing and improvement of the chatbot’s dialogue.
Lipecki, Johan, i Viggo Lundén. "The Effect of Data Quantity on Dialog System Input Classification Models". Thesis, KTH, Hälsoinformatik och logistik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-237282.
Pełny tekst źródłaDetta arbete undersöker hur olika datamängder påverkar olika slags ordvektormodeller för klassificering av indata till dialogsystem. Hypotesen att det finns ett tröskelvärde för träningsdatamängden där täta ordvektormodeller när den högsta moderna utvecklingsnivån samt att n-gram-ordvektor-klassificerare med bokstavs-noggrannhet lämpar sig särskilt väl för svenska klassificerare söks bevisas med stöd i att sammansättningar är särskilt produktiva i svenskan och att bokstavs-noggrannhet i modellerna gör att tidigare osedda ord kan klassificeras. Dessutom utvärderas hypotesen att klassificerare som tränas med enkla påståenden är bättre lämpade att klassificera indata i chattkonversationer än klassificerare som tränats med hela chattkonversationer. Resultaten stödjer ingendera hypotes utan visar istället att glesa vektormodeller presterar väldigt väl i de genomförda klassificeringstesterna. Utöver detta visar resultaten att datamängden 799 544 ord inte räcker till för att träna täta ordvektormodeller väl men att konversationer räcker gott och väl för att träna modeller för klassificering av frågor och påståenden i chattkonversationer, detta eftersom de modeller som tränats med användarindata, påstående för påstående, snarare än hela chattkonversationer, inte resulterar i bättre klassificerare för chattpåståenden.
Gligorijevic, Ilic Nemanja. "Utveckling av en FAQ chatbot - för frågor om ett program på ett universitet". Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-85197.
Pełny tekst źródłaAsher, Natali. "A Warmer Welcome : Application of a Chatbot as a Facilitator for New Hires Onboarding". Thesis, Linnéuniversitetet, Institutionen för medieteknik (ME), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-65887.
Pełny tekst źródłaLavista, Andrea. "Natural language processing: chatbot per gli studenti del Campus di Cesena". Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/19555/.
Pełny tekst źródłaWestin, Anna. "Different recipient designs with dialogue partners : An experimental comparison between a Chatbot and a Human communication partner". Thesis, Linköpings universitet, Interaktiva och kognitiva system, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-151886.
Pełny tekst źródłaFornander, Linnea. "Språklig anpassning till en artificiell dialogpartner". Thesis, Linköpings universitet, Institutionen för datavetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139246.
Pełny tekst źródłaJakúbek, Tomáš. "Chatbot k aplikácii MojiLidi". Master's thesis, 2019. http://www.nusl.cz/ntk/nusl-429093.
Pełny tekst źródłaTai, André Gilberto. "PALbot: a Plug&(Almost)pLay chatbot". Master's thesis, 2019. http://hdl.handle.net/10071/19933.
Pełny tekst źródłaA good interaction between humans and computers is built on top of each other’s characteristics, functionality and behavior. From electronics, developed through actual physical phenomena, to informatics, built on mathematical axioms, the functionality of a computer is free of human trace. While computers are known for providing correct, true and logic answers, humans spend a vast amount of time on an informal dialog with almost no purpose. In this project, a dialog system named PALbot was developed to help Ciberdúvidas platform users access information. This program simulates a human conversation answering Portuguese linguistic questions to the user. After developing the chatbot, an inquire was made to evaluate the tool in question showing the program gave a correct answer 65.54% of times with the knowledge base of Ciberdúvidas platform. Additionally, another pool of tests was made to evaluate quality attributes such as efficiency and efficacy, in which was concluded that 65.28% of the enquired agree that PALbot always and almost always makes it easy to access to the information required. The chatbot developed during the current dissertation shows high potential to improve user’s accessibility to information as well as to help Ciberdúvidas platform answering Portuguese linguistic questions.
Santos, Carlos Henrique Fernandes dos. "LEXIA: Commands Engine". Master's thesis, 2019. http://hdl.handle.net/10316/86365.
Pełny tekst źródłaAtualmente a quantidade e facilidade de acesso a informação é estonteante. Em meros momentos, uma pessoa pode-se manter atualizada sobre quaisquer tópicos de interesse. Esta facilidade de acesso mudou a perspetiva das pessoas e agora não só é a qualidade de informação disponibilizada que é valorizada, como também a velocidade a que é fornecida.Além disso, hoje em dia as pessoas tem expectativas de que informação e serviços sejam fornecidos de uma maneira fácil e intuitiva. Uma maneira de responder às expectativas das pessoas é através de assistentes virtuais. Os chatbots fornecem informação em tempo real e as interações com eles são feitas de uma forma fácil e intuitiva -- através de linguagem natural.Com a evolução das necessidades das empresas e das pessoas, a Critical Software (CSW) optou apoiar a criação de uma plataforma -- Lexia -- para o desenvolvimento de assistentes virtuais que possam interagir em vários domínios/contextos diferentes (por exemplo: podem agir como assistentes num banco ou como assistente para reservar quartos de hotel).Esta dissertação apresenta a primeira versão do Lexia. Esta primeira versão é capaz de dialogar com utilizadores e de ser implementada em vários contextos (e de executar tarefas dentro desses contextos). Usando a CSW como um caso de estudo, um agente conversacional que consegue interagir com sistemas internos desta empresa foi implementado.A versão do Lexia desenvolvida serve de fundação para possível trabalho futuro ser desenvolvido. Uma das maneiras possíveis de construir sobre esta versão é adicionando capacidades cognitivas ao sistema.
We live days in which the quantity of and rapid access to information available is staggering. In moments, a person may keep him or herself updated on topics of interest. This ease of access to information has changed people's perspectives and now, not only is the quality of information provided valued, but also the speed at which it is provided.Adding to the previous point, nowadays people expect information and services to be provided in a easy and intuitive way. A way to address the aforementioned problems is through the use of virtual assistants. Virtual assistants provide information in real-time and are interacted in a simple, intuitive way -- through natural language.With the evolution of people's and companies' needs, Critical Software (CSW) decided to go forward with the creation of a platform -- Lexia -- for developing virtual assistants that can be deployed (and execute tasks) in various different contexts/domains (e.g. deployed as an assistant in a bank or as an assistant to book hotels). This dissertation presents the first version of Lexia. This first version is capable of dialoguing with users and be deployed within various contexts (and execute tasks within those domains). Using CSW as a case study, a conversation engine that can interact with CSW's internal systems was deployed.The Lexia version developed in this internship lays the groundwork for future work to be developed. A possible way to build upon this version is to add cognitive capabilities to the platform.
Książki na temat "Chatbot dialog"
Beaven, Tita, i Fernando Rosell-Aguilar, red. Innovative language pedagogy report. Research-publishing.net, 2021. http://dx.doi.org/10.14705/rpnet.2021.50.9782490057863.
Pełny tekst źródłaCzęści książek na temat "Chatbot dialog"
Baez, Marcos, Florian Daniel i Fabio Casati. "Conversational Web Interaction: Proposal of a Dialog-Based Natural Language Interaction Paradigm for the Web". W Chatbot Research and Design, 94–110. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39540-7_7.
Pełny tekst źródłaAli, Basit, i Vadlamani Ravi. "Developing Dialog Manager in Chatbots via Hybrid Deep Learning Architectures". W Advances in Intelligent Systems and Computing, 301–10. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5679-1_28.
Pełny tekst źródłaVadász, Noémi. "Resolving Hungarian Anaphora with ChatGPT". W Text, Speech, and Dialogue, 45–57. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-40498-6_5.
Pełny tekst źródłaFergencs, Tamás, i Florian Meier. "Engagement and Usability of Conversational Search – A Study of a Medical Resource Center Chatbot". W Diversity, Divergence, Dialogue, 328–45. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71292-1_26.
Pełny tekst źródłaCallejas-Rodríguez, Ángel, Esaú Villatoro-Tello, Ivan Meza i Gabriela Ramírez-de-la-Rosa. "From Dialogue Corpora to Dialogue Systems: Generating a Chatbot with Teenager Personality for Preventing Cyber-Pedophilia". W Text, Speech, and Dialogue, 531–39. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45510-5_61.
Pełny tekst źródłaHamad, Omama, Ali Hamdi i Khaled Shaban. "Empathy and Persona of English vs. Arabic Chatbots: A Survey and Future Directions". W Text, Speech, and Dialogue, 525–37. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-16270-1_43.
Pełny tekst źródłaGotthardt, Marie, Julian Striegl, Claudia Loitsch i Gerhard Weber. "Voice Assistant-Based CBT for Depression in Students: Effects of Empathy-Driven Dialog Management". W Lecture Notes in Computer Science, 451–61. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08648-9_52.
Pełny tekst źródłaSajadieh, Sahar, i Hannen Wolfe. "Designing Interrogative Robot Theater: A Robot Who Won’t Take No for an Answer". W Creating Digitally, 183–211. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-31360-8_7.
Pełny tekst źródłaTahvanainen, Laura, Birgitta Tetri i Outi Ahonen. "Exploring and Extending Human-Centered Design to Develop AI-Enabled Wellbeing Technology in Healthcare". W Communications in Computer and Information Science, 288–306. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-59091-7_19.
Pełny tekst źródłaZgraggen, Cyril R., Sebastian B. Kunz i Kerstin Denecke. "Crowdsourcing for Creating a Dataset for Training a Medication Chatbot". W Studies in Health Technology and Informatics. IOS Press, 2021. http://dx.doi.org/10.3233/shti210364.
Pełny tekst źródłaStreszczenia konferencji na temat "Chatbot dialog"
Petukhova, Kseniia, Veronika Smilga i Dilyara Zharikova. "Abstract User Goals in Open-Domain Dialog Systems". W INTERNATIONAL CONFERENCE on Computational Linguistics and Intellectual Technologies. RSUH, 2023. http://dx.doi.org/10.28995/2075-7182-2023-22-1097-1107.
Pełny tekst źródłaAdesina, Adewala. "iNOUN Chatbot: Providing Support and Microlearning with a Web Based Conversational Smart Assistant". W Tenth Pan-Commonwealth Forum on Open Learning. Commonwealth of Learning, 2022. http://dx.doi.org/10.56059/pcf10.8217.
Pełny tekst źródłaIlievski, Vladimir, Claudiu Musat, Andreea Hossman i Michael Baeriswyl. "Goal-Oriented Chatbot Dialog Management Bootstrapping with Transfer Learning". W Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/572.
Pełny tekst źródłaSangroya, Amit, C. Anantaram, Pratik Saini i Mrinal Rawat. "Extracting Latent Beliefs and using Epistemic Reasoning to Tailor a Chatbot". W Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/860.
Pełny tekst źródłaSetiawan, Ariyono, Yuyun Suprapto, I. Gede Susrama Mas Diyasa, Chilyatun Nisa, Maulana Idris, Feronika Nur Maghfiro, Yuri Setiawan i Dama Yanti Hilda. "Design and Development of Chatbot Using Dialog Flowin Surya Sembada PDAM Surabaya City". W International Joint Conference on Science and Engineering (IJCSE 2020). Paris, France: Atlantis Press, 2020. http://dx.doi.org/10.2991/aer.k.201124.021.
Pełny tekst źródłaSudiatmika, I. Putu, i Made Ariantini. "Digital Marketing Chatbot Using API Dialog Flow Case Studi ITB Stikom Bali, Jimbaran Campus". W Proceedings of The 6th Asia-Pacific Education And Science Conference, AECon 2020, 19-20 December 2020, Purwokerto, Indonesia. EAI, 2021. http://dx.doi.org/10.4108/eai.19-12-2020.2309122.
Pełny tekst źródłaRaimer, Stephan, i Marleen Vanhauer. "Heuristic Evaluation of Public Service Chatbots". W 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1001712.
Pełny tekst źródłaCohn, Michelle, Chun-Yen Chen i Zhou Yu. "A Large-Scale User Study of an Alexa Prize Chatbot: Effect of TTS Dynamism on Perceived Quality of Social Dialog". W Proceedings of the 20th Annual SIGdial Meeting on Discourse and Dialogue. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/w19-5935.
Pełny tekst źródłaPaula, Robson T., Décio G. Aguiar Neto, Davi Romero i Paulo T. Guerra. "Evaluation of Synthetic Datasets Generation for Intent Classification Tasks in Portuguese". W Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/stil.2021.17806.
Pełny tekst źródłaIsmail, Jabri, Aboulbichr Ahmed i El ouaazizi Aziza. "Improving a Sequence-to-sequence NLP Model using a Reinforcement Learning Policy Algorithm". W 12th International Conference on Artificial Intelligence, Soft Computing and Applications. Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.122317.
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