Academic literature on the topic 'Chatbot dialogue'

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Journal articles on the topic "Chatbot dialogue"

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Fang, Jiyang. "Analysis on Chatbot Performance based on Attention Mechanism." Highlights in Science, Engineering and Technology 39 (April 1, 2023): 151–56. http://dx.doi.org/10.54097/hset.v39i.6517.

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The chatbot is a way to imitate the dialogue between people through natural language, enabling human beings to communicate with machines more naturally. The chatbot is a prevalent natural language processing task (NLP) because it has broad application prospects in real life. This is also a complex task involving many natural language processing tasks that must be studied. The chatbot is an intelligent dialogue system that can simulate human dialogue to achieve online guidance and support. The main work of this paper is to summarize the chatbot's academic background and research status and intr
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Sagstad, Mari Haaland, Nils-Halvdan Morken, Agnethe Lund, Linn Jannike Dingsør, Anne Britt Vika Nilsen, and Linn Marie Sorbye. "Quantitative User Data From a Chatbot Developed for Women With Gestational Diabetes Mellitus: Observational Study." JMIR Formative Research 6, no. 4 (2022): e28091. http://dx.doi.org/10.2196/28091.

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Background The rising prevalence of gestational diabetes mellitus (GDM) calls for the use of innovative methods to inform and empower these pregnant women. An information chatbot, Dina, was developed for women with GDM and is Norway’s first health chatbot, integrated into the national digital health platform. Objective The aim of this study is to investigate what kind of information users seek in a health chatbot providing support on GDM. Furthermore, we sought to explore when and how the chatbot is used by time of day and the number of questions in each dialogue and to categorize the question
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Tsai, Wan-Hsiu Sunny, Yu Liu, and 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, no. 3 (2021): 460–82. http://dx.doi.org/10.1108/jrim-12-2019-0200.

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PurposeThis study presents one of the earliest empirical investigations on how brand chatbots' anthropomorphic design and social presence communication strategies may improve consumer evaluation outcomes via the mediators of parasocial interaction and perceived dialogue.Design/methodology/approachThis study employs a 2 (high vs. low social presence communication) by 2 (anthropomorphic vs. non-anthropomorphic bot profile) between-subject experimental design to evaluate how chatbots' high social presence communication and anthropomorphic profile design may enhance perceptions of parasocial inter
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Lin, Chien-Chang, Anna Y. Q. Huang, and Stephen J. H. Yang. "A Review of AI-Driven Conversational Chatbots Implementation Methodologies and Challenges (1999–2022)." Sustainability 15, no. 5 (2023): 4012. http://dx.doi.org/10.3390/su15054012.

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A conversational chatbot or dialogue system is a computer program designed to simulate conversation with human users, especially over the Internet. These chatbots can be integrated into messaging apps, mobile apps, or websites, and are designed to engage in natural language conversations with users. There are also many applications in which chatbots are used for educational support to improve students’ performance during the learning cycle. The recent success of ChatGPT also encourages researchers to explore more possibilities in the field of chatbot applications. One of the main benefits of c
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Gregorcic, Bor, and Ann-Marie Pendrill. "ChatGPT and the frustrated Socrates." Physics Education 58, no. 3 (2023): 035021. http://dx.doi.org/10.1088/1361-6552/acc299.

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Abstract We present a case study of a conversation between ourselves and an artificial intelligence-based chatbot ChatGPT. We asked the chatbot to respond to a basic physics question that will be familiar to most physics teachers: ‘A teddy bear is thrown into the air. What is its acceleration in the highest point?’ The chatbot’s responses, while linguistically quite advanced, were unreliable in their correctness and often full of contradictions. We then attempted to engage in Socratic dialogue with the chatbot to resolve the errors and contradictions, but with little success. We found that Cha
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Kumar, Kartik. "An Educational Chatbot Using AI in Radiotherapy." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem34122.

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The surge in demand for information in cancer centers and hospitals, particularly during the pandemic, overwhelmed the limited manpower available. To address this challenge, there arose a need to develop an educational chatbot tailored for diverse user groups in the field of radiotherapy, including patients and their families, the general public, and radiation staff. Objective: In response to the pressing clinical demands, the primary aim of this endeavor is to delve into the intricacies of designing an educational chatbot for radiotherapy using artificial intelligence.Methods: The chatbot is
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Li, Jingquan. "Security Implications of AI Chatbots in Health Care." Journal of Medical Internet Research 25 (November 28, 2023): e47551. http://dx.doi.org/10.2196/47551.

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Artificial intelligence (AI) chatbots like ChatGPT and Google Bard are computer programs that use AI and natural language processing to understand customer questions and generate natural, fluid, dialogue-like responses to their inputs. ChatGPT, an AI chatbot created by OpenAI, has rapidly become a widely used tool on the internet. AI chatbots have the potential to improve patient care and public health. However, they are trained on massive amounts of people’s data, which may include sensitive patient data and business information. The increased use of chatbots introduces data security issues,
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Černý, Michal. "Educational Psychology Aspects of Learning with Chatbots without Artificial Intelligence: Suggestions for Designers." European Journal of Investigation in Health, Psychology and Education 13, no. 2 (2023): 284–305. http://dx.doi.org/10.3390/ejihpe13020022.

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Chatbots without artificial intelligence can play the role of practical and easy-to-implement learning objects in e-learning environments, allowing a reduction in social or psychological isolation. This research, with a sample of 79 students, explores the principles that need to be followed in designing this kind of chatbot in education in order to ensure an acceptable outcome for students. Research has shown that students interacting with a chatbot without artificial intelligence expect similar psychological and communicative responses to those of a live human, project the characteristics of
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Shawar, Bayan Abu, and Eric Steven Atwell. "Using corpora in machine-learning chatbot systems." International Journal of Corpus Linguistics 10, no. 4 (2005): 489–516. http://dx.doi.org/10.1075/ijcl.10.4.06sha.

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A chatbot is a machine conversation system which interacts with human users via natural conversational language. Software to machine-learn conversational patterns from a transcribed dialogue corpus has been used to generate a range of chatbots speaking various languages and sublanguages including varieties of English, as well as French, Arabic and Afrikaans. This paper presents a program to learn from spoken transcripts of the Dialogue Diversity Corpus of English, the Minnesota French Corpus, the Corpus of Spoken Afrikaans, the Qur'an Arabic-English parallel corpus, and the British National Co
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Bodapati, Mrs Nagaeswari. "Campus Companion : Creating a Supportive Chat – Assistant for Students." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem29939.

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This article explores the creation and usage of chatbots, or intelligent conversational agents, for online communication. Python and other machine learning methods are employed in the chatbot's design. To be more explicit, TensorFlow/Keras is used for natural language processing, MySQL is utilized for database administration, and Flask is used for web hosting. The initiative attempts to accomplish its goals by enhancing the user experience and fostering more effective communication on the website. Using massive datasets, the chatbot will be educated to comprehend users' objectives and offer re
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Dissertations / Theses on the topic "Chatbot dialogue"

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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.

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A chatbot is a computer program that engages in written or spoken conversation with a human user. This project aims to investigate the possibility of training a chatbot in using movie dialogue in generating the response. Movie dialogue can be found in both movie scripts as well as subtitles, though using subtitles is much easier as they follow a special formatting. Using one subtitle as a response to each word found in the preceding subtitle, the implemented chatbot links together subtitles. The responses are stored in a frequency distribution table that maps each word to all responses found.
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Bouguelia, 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.

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Les Systèmes de Dialogue (ou simplement chatbots) sont très demandés de nos jours. Ils permettent de comprendre les besoins des utilisateurs (ou intentions des utilisateurs), exprimés en langage naturel, et de répondre à ces intentions en invoquant les APIs (Interfaces de Programmation d’Application) appropriées. Les chatbots sont connus pour leur interface facile à utiliser et ils ne nécessitent que l'une des capacités les plus innées des humains qui est l'utilisation du langage naturel. L'amélioration continue de l'Intelligence Artificielle (IA), du Traitement du Langage Naturel (NLP) et du
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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.

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Motivée par le gain en popularité des chatbots prenant le rôle de conseillers sur les sites Web des entreprises, cette thèse s'attaque au problème de la détection des problèmes d’interaction entre un conseiller virtuel et ses utilisateurs sous l'angle de l'analyse des opinions et des émotions dans les textes. Cette thèse s’est déroulée dans le cadre d’une application concrète pour l’entreprise EDF et s'est appuyée sur le corpus du chatbot d'EDF. Ce corpus regroupe des expressions spontanées et riches, collectées dans les conditions écologiques (parfois appelées « in-the-wild »), difficiles à a
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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.

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Chatbots are becoming more common in modern society, but there are almost no studies that explore both the differences and causes that divides human communication from communication with a chatbot. The aim of this thesis was to explore different recipient design people take when communicating with a human and a chatbot. A chatbot was built and an experiment was conducted that measured the performance and experience of the participants. A thematic analysis then found out causes for these experiences. The study focused on finding new differences in addition to exploring people’s boredom, frustra
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Asher, 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.

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Despite being explored and constantly improved through the years, onboarding of new hires in corporate organizations has remained a challenge. Many of the issues can be linked to a lack of communication between the organization and the new employee, as well as the common nature of these environments where information is spread across job titles and sources. This thesis discusses the feasibility of implementing a basic chatbot that will allow new hires to ask questions and request varied information at all times, using an interface such as a messaging app. This research explores the way chatbot
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Kero, Chanelle, and 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.

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Automatisering av kundtjänster genom implementering av chatbotar blir allt vanligare för att kunna erbjuda kunder en mer tillgänglig och effektiv service. Vid implementering av chatbotar i kundtjänster lämnas den mänskliga kontrollen och kundens upplevelse delvis över till ett digitalt system, vilket ställer krav på utformning av chatbotars dialoger. Syftet med arbetet är att ta fram en artefakt i form av en chatbot och utveckla dess dialog för en framtida implementation i en kundtjänst. Arbetet ämnar att ta fram designprinciper för utformning och utveckling av chatbotar och deras dialoger i e
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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.

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The implementation of chatbots and service services is becoming more common. The reason for this is that they are constantly available to answer questions, no matter what time it is. To make one chatbot is not just to write questions and specific answers. Communicating with one chatbot should, as much as possible, look like communicating with another human. The purpose of this report is to create a chatbot that will be used at Luleå university of technology and that will answer questions about system science. Furthermore, the goal is to investigate which design principles should be implemente
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Lavista, 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/.

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Il natural language processing è un campo di ricerca interdisciplinare che spazia tra informatica, linguistica e intelligenza artificiale, che si pone come obiettivo il trattamento automatico del linguaggio naturale, ovvero l’analisi, la comprensione e l’elaborazione del linguaggio da parte dei calcolatori. Uno dei problemi più interessanti e ancora aperti di questa disciplina è la capacità di dialogo per la quale ricercatori e studiosi stanno ideando e impiegando nuovi approcci, in particolare basati su reti neurali artificiali, raggiungendo risultati sempre migliori. In questa tesi, oltre a
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Lipecki, Johan, and 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.

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This paper researches how different amounts of data affect different word vector models for classification of dialog system user input. A hypothesis is tested that there is a data threshold for dense vector models to reach the state-of-the-art performance that have been shown with recent research, and that character-level n-gram word-vector classifiers are especially suited for Swedish classifiers–because of compounding and the character-level n-gram model ability to vectorize out-of-vocabulary words. Also, a second hypothesis is put forward that models trained with single statements are more
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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.

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Trots att antalet medier via vilka vi människor kan kommunicera med varandra är högre än någonsin, är talad interaktion något unikt betydelsefullt för våra mänskliga samhällen och relationer och därför ett ständigt relevant forskningsområde. Denna studie undersökte kvantitativa skillnader i hur människor konverserar med en talbaserad chattbot jämfört med en mänsklig konversationspartner, då de utförde en uppgift utformad för att skapa jämförliga dialoger. Resultatet visade på att konversationerna med chattbotten var mindre effektiva och ledde till sämre prestation i uppgiften. Dessutom påvisad
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Books on the topic "Chatbot dialogue"

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McTear, Michael. Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots. Springer International Publishing AG, 2020.

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McTear, Michael. Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots. Morgan & Claypool Publishers, 2020.

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McTear, Michael. Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots. Morgan & Claypool Publishers, 2020.

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McTear, Michael. Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots. Morgan & Claypool Publishers, 2020.

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Galley, Michel, Jianfeng Gao, and Lihong Li. Neural Approaches to Conversational AI: Question Answering, Task-Oriented Dialogues and Social Chatbots. Now Publishers, 2019.

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Beaven, Tita, and Fernando Rosell-Aguilar, eds. Innovative language pedagogy report. Research-publishing.net, 2021. http://dx.doi.org/10.14705/rpnet.2021.50.9782490057863.

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The Innovative Language Pedagogy Report presents new and emerging approaches to language teaching, learning, and assessment in school, further education, and higher education settings. Researchers and practitioners provide 22 research-informed, short articles on their chosen pedagogy, with examples and resources. The report is jargon-free, written in a readable format, and covers, among others, gamification, open badges, comparative judgement, translanguaging, translation, learning without a teacher, and dialogue facilitation. It also includes technologies such as chatbots, augmented reality,
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Book chapters on the topic "Chatbot dialogue"

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Lobo, Inês, Diogo Rato, Rui Prada, and Frank Dignum. "Socially Aware Interactions: From Dialogue Trees to Natural Language Dialogue Systems." In Chatbot Research and Design. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94890-0_8.

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Yildiz, Eren, Suna Bensch, and Frank Dignum. "Incorporating Social Practices in Dialogue Systems." In Chatbot Research and Design. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94890-0_7.

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Tegos, Stergios, Stavros Demetriadis, Georgios Psathas, and Thrasyvoulos Tsiatsos. "A Configurable Agent to Advance Peers’ Productive Dialogue in MOOCs." In Chatbot Research and Design. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39540-7_17.

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Fergencs, Tamás, and Florian Meier. "Engagement and Usability of Conversational Search – A Study of a Medical Resource Center Chatbot." In Diversity, Divergence, Dialogue. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71292-1_26.

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Yuwono, Steven Kester, Biao Wu, and Luis Fernando D’Haro. "Automated Scoring of Chatbot Responses in Conversational Dialogue." In Lecture Notes in Electrical Engineering. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9443-0_31.

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Assayed, Suha Khalil, Manar Alkhatib, and Khaled Shaalan. "The Key Challenges in Educational Advising Chatbot Dialogue System." In Innovation in the University 4.0 System based on Smart Technologies. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003425809-5.

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Callejas-Rodríguez, Ángel, Esaú Villatoro-Tello, Ivan Meza, and Gabriela Ramírez-de-la-Rosa. "From Dialogue Corpora to Dialogue Systems: Generating a Chatbot with Teenager Personality for Preventing Cyber-Pedophilia." In Text, Speech, and Dialogue. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45510-5_61.

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Matsuura, Shu, and Riki Ishimura. "Chatbot and Dialogue Demonstration with a Humanoid Robot in the Lecture Class." In Universal Access in Human–Computer Interaction. Human and Technological Environments. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58700-4_20.

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Li, Junmei. "Multi-round Dialogue Intention Recognition Method for a Chatbot Baed on Deep Learning." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-18123-8_44.

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Galitsky, Boris. "Discourse-Level Dialogue Management." In Developing Enterprise Chatbots. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04299-8_11.

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Conference papers on the topic "Chatbot dialogue"

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Ismail, Jabri, Aboulbichr Ahmed, and El ouaazizi Aziza. "Improving a Sequence-to-sequence NLP Model using a Reinforcement Learning Policy Algorithm." In 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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Nowadays, the current neural network models of dialogue generation(chatbots) show great promise for generating answers for chatty agents. But they are short-sighted in that they predict utterances one at a time while disregarding their impact on future outcomes. Modelling a dialogue’s future direction is critical for generating coherent, interesting dialogues, a need that has led traditional NLP dialogue models that rely on reinforcement learning. In this article, we explain how to combine these objectives by using deep reinforcement learning to predict future rewards in chatbot dialogue. The
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Galitsky, Boris, Dmitry Ilvovsky, and Elizaveta Goncharova. "On a Chatbot Conducting Dialogue-in-Dialogue." In Proceedings of the 20th Annual SIGdial Meeting on Discourse and Dialogue. Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/w19-5916.

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Raimer, Stephan, and Marleen Vanhauer. "Heuristic Evaluation of Public Service Chatbots." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1001712.

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In recent years, chatbots have been adopted in business contexts and also for public services at a growing rate. Chatbots provide dialogue interfaces combining visual elements with natural conversation. Good Conversational Design in this context covers the topics of Natural-Language Processing (NLP) and Dialogue Management (DM). Few attention has been paid to the usability evaluation of conversational interfaces (Höhn & Bongard-Blanchy, 2021). The present paper builds upon the work by Höhn & Bongard-Blanchy by applying their framework of conversational heuristics to evaluate a set of p
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Paula, Robson T., Décio G. Aguiar Neto, Davi Romero, and Paulo T. Guerra. "Evaluation of Synthetic Datasets Generation for Intent Classification Tasks in Portuguese." In Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/stil.2021.17806.

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A chatbot is an artificial intelligence based system aimed at chatting with users, commonly used as a virtual assistant to help people or answer questions. Intent classification is an essential task for chatbots where it aims to identify what the user wants in a certain dialogue. However, for many domains, little data are available to properly train those systems. In this work, we evaluate the performance of two methods to generate synthetic data for chatbots, one based on template questions and another based on neural text generation. We build four datasets that are used training chatbot comp
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Hancock, Braden, Antoine Bordes, Pierre-Emmanuel Mazare, and Jason Weston. "Learning from Dialogue after Deployment: Feed Yourself, Chatbot!" In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/p19-1358.

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Galitsky, Boris, and Dmitry Ilvovsky. "Chatbot with a Discourse Structure-Driven Dialogue Management." In Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, 2017. http://dx.doi.org/10.18653/v1/e17-3022.

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Kao, Chien-Hao, Chih-Chieh Chen, and Yu-Tza Tsai. "Model of Multi-turn Dialogue in Emotional Chatbot." In 2019 International Conference on Technologies and Applications of Artificial Intelligence (TAAI). IEEE, 2019. http://dx.doi.org/10.1109/taai48200.2019.8959855.

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Ilievski, Vladimir, Claudiu Musat, Andreea Hossman, and Michael Baeriswyl. "Goal-Oriented Chatbot Dialog Management Bootstrapping with Transfer Learning." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/572.

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Goal-Oriented (GO) Dialogue Systems, colloquially known as goal oriented chatbots, help users achieve a predefined goal (e.g. book a movie ticket) within a closed domain. A first step is to understand the user's goal by using natural language understanding techniques. Once the goal is known, the bot must manage a dialogue to achieve that goal, which is conducted with respect to a learnt policy. The success of the dialogue system depends on the quality of the policy, which is in turn reliant on the availability of high-quality training data for the policy learning method, for instance Deep Rein
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Wu, Shih-Hung, Liang-Pu Chen, Ping-Che Yang, and Tsun Ku. "Automatic Dialogue Template Synthesis for Chatbot by Story Information Extraction." In 2018 IEEE International Conference on Information Reuse and Integration for Data Science (IRI). IEEE, 2018. http://dx.doi.org/10.1109/iri.2018.00077.

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Lee, Seugnjun, Yoonna Jang, Chanjun Park, et al. "PEEP-Talk: A Situational Dialogue-based Chatbot for English Education." In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations). Association for Computational Linguistics, 2023. http://dx.doi.org/10.18653/v1/2023.acl-demo.18.

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