Gotowa bibliografia na temat „Chatbot dialogue”
Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych
Spis treści
Zobacz listy aktualnych artykułów, książek, rozpraw, streszczeń i innych źródeł naukowych na temat „Chatbot dialogue”.
Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.
Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.
Artykuły w czasopismach na temat "Chatbot dialogue"
Fang, 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 źródłaSagstad, Mari Haaland, Nils-Halvdan Morken, Agnethe Lund, Linn Jannike Dingsør, Anne Britt Vika Nilsen i Linn Marie Sorbye. "Quantitative User Data From a Chatbot Developed for Women With Gestational Diabetes Mellitus: Observational Study". JMIR Formative Research 6, nr 4 (18.04.2022): e28091. http://dx.doi.org/10.2196/28091.
Pełny tekst źródłaTsai, Wan-Hsiu Sunny, Yu Liu i Ching-Hua Chuan. "How chatbots' social presence communication enhances consumer engagement: the mediating role of parasocial interaction and dialogue". Journal of Research in Interactive Marketing 15, nr 3 (18.06.2021): 460–82. http://dx.doi.org/10.1108/jrim-12-2019-0200.
Pełny tekst źródłaLin, Chien-Chang, Anna Y. Q. Huang i Stephen J. H. Yang. "A Review of AI-Driven Conversational Chatbots Implementation Methodologies and Challenges (1999–2022)". Sustainability 15, nr 5 (22.02.2023): 4012. http://dx.doi.org/10.3390/su15054012.
Pełny tekst źródłaGregorcic, Bor, i Ann-Marie Pendrill. "ChatGPT and the frustrated Socrates". Physics Education 58, nr 3 (22.03.2023): 035021. http://dx.doi.org/10.1088/1361-6552/acc299.
Pełny tekst źródłaKumar, Kartik. "An Educational Chatbot Using AI in Radiotherapy". INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, nr 05 (16.05.2024): 1–5. http://dx.doi.org/10.55041/ijsrem34122.
Pełny tekst źródłaLi, Jingquan. "Security Implications of AI Chatbots in Health Care". Journal of Medical Internet Research 25 (28.11.2023): e47551. http://dx.doi.org/10.2196/47551.
Pełny tekst źródłaČerný, Michal. "Educational Psychology Aspects of Learning with Chatbots without Artificial Intelligence: Suggestions for Designers". European Journal of Investigation in Health, Psychology and Education 13, nr 2 (28.01.2023): 284–305. http://dx.doi.org/10.3390/ejihpe13020022.
Pełny tekst źródłaShawar, Bayan Abu, i Eric Steven Atwell. "Using corpora in machine-learning chatbot systems". International Journal of Corpus Linguistics 10, nr 4 (7.11.2005): 489–516. http://dx.doi.org/10.1075/ijcl.10.4.06sha.
Pełny tekst źródłaBodapati, Mrs Nagaeswari. "Campus Companion : Creating a Supportive Chat – Assistant for Students". INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, nr 04 (2.04.2024): 1–5. http://dx.doi.org/10.55041/ijsrem29939.
Pełny tekst źródłaRozprawy doktorskie na temat "Chatbot dialogue"
Roghult, Alexander. "Chatbot trained on movie dialogue". Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-157637.
Pełny tekst źródłaBouguelia, Sara. "Modèles de dialogue et reconnaissance d'intentions composites dans les conversations Utilisateur-Chatbot orientées tâches". Electronic Thesis or Diss., Lyon 1, 2023. http://www.theses.fr/2023LYO10106.
Pełny tekst źródłaDialogue Systems (or simply chatbots) are in very high demand these days. They enable the understanding of user needs (or user intents), expressed in natural language, and on fulfilling such intents by invoking the appropriate back-end APIs (Application Programming Interfaces). Chatbots are famed for their easy-to-use interface and gentle learning curve (it only requires one of humans' most innate ability, the use of natural language). The continuous improvement in Artificial Intelligence (AI), Natural Language Processing (NLP), and the countless number of devices allow performing real-world tasks (e.g., making a reservation) by using natural language-based interactions between users and a large number of software enabled services.Nonetheless, chatbot development is still in its preliminary stage, and there are several theoretical and technical challenges that need to be addressed. One of the challenges stems from the wide range of utterance variations in open-end human-chatbot interactions. Additionally, there is a vast space of software services that may be unknown at development time. Natural human conversations can be rich, potentially ambiguous, and express complex and context-dependent intents. Traditional business process and service composition modeling and orchestration techniques are limited to support such conversations because they usually assume a priori expectation of what information and applications will be accessed and how users will explore these sources and services. Limiting conversations to a process model means that we can only support a small fraction of possible conversations. While existing advances in NLP and Machine Learning (ML) techniques automate various tasks such as intent recognition, the synthesis of API calls to support a broad range of potentially complex user intents is still largely a manual, ad-hoc and costly process.This thesis project aims at advancing the fundamental understanding of cognitive services engineering. In this thesis we contribute novel abstractions and techniques focusing on the synthesis of API calls to support a broad range of potentially complex user intents. We propose reusable and extensible techniques to recognize and realize complex intents during humans-chatbots-services interactions. These abstractions and techniques seek to unlock the seamless and scalable integration of natural language-based conversations with software-enabled services
Poltavchenko, Irina. "De l'analyse d'opinions à la détection des problèmes d'interactions humain-machine : application à la gestion de la relation client". Electronic Thesis or Diss., Paris, ENST, 2018. http://www.theses.fr/2018ENST0030.
Pełny tekst źródłaThis PHD thesis is motivated by the growing popularity of chatbots acting as advisors on corporate websites. This research addresses the detection of the interaction problems between a virtual advisor and its users from the angle of opinion and emotion analysis in the texts. The present study takes place in the concrete application context of a French energy supplier EDF, using EDF chatbot corpus. This corpus gathers spontaneous and rich expressions, collected in "in-the-wild" conditions, difficult to analyze automatically, and still little studied. We propose a typology of interaction problems and annotate a part of the corpus according to this typology. A part of created annotation is used to evaluate the system. The system named DAPI (automatic detection of interaction problems) developed during this thesis is a hybrid system that combines the symbolic approach and the unsupervised learning of semantic representation (word embeddings). The purpose of the DAPI system is to be directly connected to the chatbot and to detect online interaction problems as soon as a user statement is received. The originality of the proposed method is based on : i) taking into account the history of the dialogue ; ii) the modeling of interaction problems as the expressions of user spontaneous opinion or emotion towards the interaction ; iii) the integration of the web-chat and in-the-wild language specificities as linguistic cues for linguistic rules ; iv) use of lexical word embedding (word2vec) learned on the large untagged chatbot corpus to model semantic similarities. The results obtained are very encouraging considering the complexity of the data : F-score = 74.3%
Westin, 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 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 źródłaKero, 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.
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 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 źródłaLipecki, 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.
Fornander, 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 źródłaKsiążki na temat "Chatbot dialogue"
McTear, Michael. Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots. Springer International Publishing AG, 2020.
Znajdź pełny tekst źródłaMcTear, Michael. Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots. Morgan & Claypool Publishers, 2020.
Znajdź pełny tekst źródłaMcTear, Michael. Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots. Morgan & Claypool Publishers, 2020.
Znajdź pełny tekst źródłaMcTear, Michael. Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots. Morgan & Claypool Publishers, 2020.
Znajdź pełny tekst źródłaGalley, Michel, Jianfeng Gao i Lihong Li. Neural Approaches to Conversational AI: Question Answering, Task-Oriented Dialogues and Social Chatbots. Now Publishers, 2019.
Znajdź pełny tekst źródłaBeaven, 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 dialogue"
Lobo, Inês, Diogo Rato, Rui Prada i Frank Dignum. "Socially Aware Interactions: From Dialogue Trees to Natural Language Dialogue Systems". W Chatbot Research and Design, 124–40. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94890-0_8.
Pełny tekst źródłaYildiz, Eren, Suna Bensch i Frank Dignum. "Incorporating Social Practices in Dialogue Systems". W Chatbot Research and Design, 108–23. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94890-0_7.
Pełny tekst źródłaTegos, Stergios, Stavros Demetriadis, Georgios Psathas i Thrasyvoulos Tsiatsos. "A Configurable Agent to Advance Peers’ Productive Dialogue in MOOCs". W Chatbot Research and Design, 245–59. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39540-7_17.
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 źródłaYuwono, Steven Kester, Biao Wu i Luis Fernando D’Haro. "Automated Scoring of Chatbot Responses in Conversational Dialogue". W Lecture Notes in Electrical Engineering, 357–69. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9443-0_31.
Pełny tekst źródłaAssayed, Suha Khalil, Manar Alkhatib i Khaled Shaalan. "The Key Challenges in Educational Advising Chatbot Dialogue System". W Innovation in the University 4.0 System based on Smart Technologies, 74–82. Boca Raton: Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003425809-5.
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 źródłaMatsuura, Shu, i Riki Ishimura. "Chatbot and Dialogue Demonstration with a Humanoid Robot in the Lecture Class". W Universal Access in Human–Computer Interaction. Human and Technological Environments, 233–46. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58700-4_20.
Pełny tekst źródłaLi, Junmei. "Multi-round Dialogue Intention Recognition Method for a Chatbot Baed on Deep Learning". W Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 561–72. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-18123-8_44.
Pełny tekst źródłaGalitsky, Boris. "Discourse-Level Dialogue Management". W Developing Enterprise Chatbots, 365–426. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04299-8_11.
Pełny tekst źródłaStreszczenia konferencji na temat "Chatbot dialogue"
Ismail, 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.
Pełny tekst źródłaGalitsky, Boris, Dmitry Ilvovsky i Elizaveta Goncharova. "On a Chatbot Conducting Dialogue-in-Dialogue". 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/w19-5916.
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 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 źródłaHancock, Braden, Antoine Bordes, Pierre-Emmanuel Mazare i Jason Weston. "Learning from Dialogue after Deployment: Feed Yourself, Chatbot!" W Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/p19-1358.
Pełny tekst źródłaGalitsky, Boris, i Dmitry Ilvovsky. "Chatbot with a Discourse Structure-Driven Dialogue Management". W Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2017. http://dx.doi.org/10.18653/v1/e17-3022.
Pełny tekst źródłaKao, Chien-Hao, Chih-Chieh Chen i Yu-Tza Tsai. "Model of Multi-turn Dialogue in Emotional Chatbot". W 2019 International Conference on Technologies and Applications of Artificial Intelligence (TAAI). IEEE, 2019. http://dx.doi.org/10.1109/taai48200.2019.8959855.
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 źródłaWu, Shih-Hung, Liang-Pu Chen, Ping-Che Yang i Tsun Ku. "Automatic Dialogue Template Synthesis for Chatbot by Story Information Extraction". W 2018 IEEE International Conference on Information Reuse and Integration for Data Science (IRI). IEEE, 2018. http://dx.doi.org/10.1109/iri.2018.00077.
Pełny tekst źródłaLee, Seugnjun, Yoonna Jang, Chanjun Park, Jungseob Lee, Jaehyung Seo, Hyeonseok Moon, Sugyeong Eo, Seounghoon Lee, Bernardo Yahya i Heuiseok Lim. "PEEP-Talk: A Situational Dialogue-based Chatbot for English Education". W Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations). Stroudsburg, PA, USA: Association for Computational Linguistics, 2023. http://dx.doi.org/10.18653/v1/2023.acl-demo.18.
Pełny tekst źródła