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Journal articles on the topic 'Conversational agent chatbots'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Qin, Zhen (Luther). "Conversational Breakdown Detector for a Motivational Interviewing Conversational Agent." IJournal: Student Journal of the Faculty of Information 9, no. 1 (2023): 60–77. http://dx.doi.org/10.33137/ijournal.v9i1.42237.

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A conversational breakdown in human-chatbot interaction refers to a disruption or failure in the communicative flow between the human user and the chatbot. To recover a disrupted conversation, the first step is to detect the breakdown. Researchers have proposed methods using supervised learning and semi-supervised learning in dialogue systems to achieve the goal of detecting conversational breakdown. However, few studies have focused on detecting breakdowns in automated therapeutic conversations, especially conversations led by motivational interviewing chatbots. The presence of conversational

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L, Manigandan, and Sivakumar Alur. "Mapping the Research Landscape of Chatbots, Conversational Agents, and Virtual Assistants in Business, Management, and Accounting: A Bibliometric Review." Qubahan Academic Journal 3, no. 4 (2023): 502–13. http://dx.doi.org/10.58429/qaj.v3n4a252.

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This bibliometric review aims to map the research landscape of chatbots, conversational agents, and virtual assistants in the business, management, and accounting of the subject area. The review begins by examining the growth of research in this area over time, revealing an increasing interest in the application of chatbots, conversational agents, and virtual assistants in business, management, and accounting contexts. This study aims to contribute to the field of chatbot research by conducting a bibliometric analysis of chatbot, conversational agent and virtual assistant papers available in t

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Jiang, Zhiqiu, Mashrur Rashik, Kunjal Panchal, et al. "CommunityBots: Creating and Evaluating A Multi-Agent Chatbot Platform for Public Input Elicitation." Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (2023): 1–32. http://dx.doi.org/10.1145/3579469.

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In recent years, the popularity of AI-enabled conversational agents or chatbots has risen as an alternative to traditional online surveys to elicit information from people. However, there is a gap in using single-agent chatbots to converse and gather multi-faceted information across a wide variety of topics. Prior works suggest that single-agent chatbots struggle to understand user intentions and interpret human language during a multi-faceted conversation. In this work, we investigated how multi-agent chatbot systems can be utilized to conduct a multi-faceted conversation across multiple doma

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Omarov, Batyrkhan, Sergazi Narynov, Zhandos Zhumanov, Elmira Alzhanova, Aidana Gumar, and Mariyam Khassanova. "Artificial intelligence enabled conversational agent for mental healthcare." International journal of health sciences 6, no. 3 (2022): 1544–55. http://dx.doi.org/10.53730/ijhs.v6n3.13239.

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Conversational agents are a software program that can converse with users in the manner of a real-world conversation. Artificial intelligence (AI) is not complete without conversation modeling. The most difficult artificial intelligence endeavor since its start has been developing an effective chatbot application. Despite chatbots may do a variety of tasks, their main duty is to accurately understand human speech and respond appropriately. Previously, manual patterns and instructions or simple statistical methods were used to create chatbots architectures. Due to its improved capacity for trai

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Bennion, Matthew Russell, Gillian E. Hardy, Roger K. Moore, Stephen Kellett, and Abigail Millings. "Usability, Acceptability, and Effectiveness of Web-Based Conversational Agents to Facilitate Problem Solving in Older Adults: Controlled Study." Journal of Medical Internet Research 22, no. 5 (2020): e16794. http://dx.doi.org/10.2196/16794.

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Background The usability and effectiveness of conversational agents (chatbots) that deliver psychological therapies is under-researched. Objective This study aimed to compare the system usability, acceptability, and effectiveness in older adults of 2 Web-based conversational agents that differ in theoretical orientation and approach. Methods In a randomized study, 112 older adults were allocated to 1 of the following 2 fully automated interventions: Manage Your Life Online (MYLO; ie, a chatbot that mimics a therapist using a method of levels approach) and ELIZA (a chatbot that mimics a therapi

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Belainine, Billal, Fatiha Sadat, and Hakim Lounis. "Modelling a Conversational Agent with Complex Emotional Intelligence." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 10 (2020): 13710–11. http://dx.doi.org/10.1609/aaai.v34i10.7127.

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Chatbots or conversational agents have enjoyed great popularity in recent years. They surprisingly perform sensitive tasks in modern societies. However, despite the fact that they offer help, support, and fellowship, there is a task that is not yet mastered: dealing with complex emotions and simulating human sensations. This research aims to design an architecture for an emotional conversation agent for long-text conversations (multi-turns). This agent is intended to work in areas where the analysis of users feelings plays a leading role. This work refers to natural language understanding and

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Muhammad Bilal Ahmad Jamil and Duryab Shahzadi. "A systematic review A Conversational interface agent for the export business acceleration." Lahore Garrison University Research Journal of Computer Science and Information Technology 7, no. 02 (2023): 37–49. http://dx.doi.org/10.54692/lgurjcsit.2023.0702430.

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Conversational agents, which understand, respond to, and learn from each interaction using Automatic Speech Recognition (ASR), Natural Language Processing (NLP), Advanced Dialog Management, and Machine Learning (ML), have become more common in recent years. Conversational agents, also referred to as chatbots, are used to have real-time conversations with individuals. As a result, conversational agents are now being used in a variety of sectors, including those in education, healthcare, marketing, customer assistance, and entertainment. Conversational agents, which are frequently used as chatbo

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Chen, Jengchung Victor, Huyen Thi Le, and Sinh Thi Thu Tran. "Understanding automated conversational agent as a decision aid: matching agent's conversation with customer's shopping task." Internet Research 31, no. 4 (2021): 1376–404. http://dx.doi.org/10.1108/intr-11-2019-0447.

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PurposeTo provide better services to customers, especially immediate responses and 24/7 availability, businesses are implementing text-based automated conversational agents, i.e. chatbots on their social platforms and websites. Chatbots are required to not only provide customers with necessary consultancy and guidance but also communicate friendly and socially. Based on the cognitive fit theory, this study attempts to examine the role of chatbot as a decision aid and how the match between information presentation in forms of decisional guidance and communication style and the shopping task inf

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Araujo, Theo. "Conversational Agent Research Toolkit : An alternative for creating and managing chatbots for experimental research1." Computational Communication Research 2, no. 1 (2020): 35–51. http://dx.doi.org/10.5117/ccr2020.1.002.arau.

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Abstract Conversational agents in the form of chatbots available in messaging platforms are gaining increasing relevance in our communication environment. Based on natural language processing and generation techniques, they are built to automatically interact with users in several contexts. We present here a tool, the Conversational Agent Research Toolkit (CART), aimed at enabling researchers to create conversational agents for experimental studies. CART integrates existing APIs frequently used in practice and provides functionality that allows researchers to create and manage multiple version

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Inupakutika, D., M. Nadim, G. R. Gunnam, et al. "Integration of NLP and Speech-to-text Applications with Chatbots." Electronic Imaging 2021, no. 3 (2021): 35–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.3.mobmu-035.

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With the evolving artificial intelligence technology, the chatbots are becoming smarter and faster lately. Chatbots are typically available round the clock providing continuous support and services. A chatbot or a conversational agent is a program or software that can communicate using natural language with humans. The challenge of developing an intelligent chatbot still exists ever since the onset of artificial intelligence. The functionality of chatbots can range from business oriented short conversations to healthcare intervention based longer conversations. However, the primary role that t

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Khan, Imran ullah, Junaid Javed, Ahthasham Sajid, Shahnoor, and Iqra Tabassum. "Comparative Analysis of Classical and Neural Networks based ChatBot’s Techniques." Sir Syed University Research Journal of Engineering & Technology 13, no. 1 (2023): 61–73. http://dx.doi.org/10.33317/ssurj.508.

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Conversational agents like Alexa from Amazon, Siri from Apple, Assistant from Google, and Cortana from Microsoft demonstrate extraordinary research and potential in conversational agents. A conversational agent, chatter-bot, or chatbot is a piece of computer software supposed to communicate at a level of intelligence comparable to a person's. Chatbots are designed for various purposes, such as task-oriented helpers and creators of open-ended discourse. Numerous approaches have been studied, from primitive types of hard-coded response generators to contemporary ways of constructing artificial i

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Kapuskar, Vaibhavi, Sakshi Bobade, Srushti Diwan, Akshata Dholwade, Vaishnavi Kamble, and Prof S. R. Gudadhe. "Efficient Chatbot Designing." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (2022): 2743–45. http://dx.doi.org/10.22214/ijraset.2022.41889.

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Abstract: A conversational agent (chatbot) is a piece of software that is able to communicate with humans using natural language. Modeling conversation is an important task in natural language processing and artificial intelligence (AI). Indeed, ever since the birth of AI, creating a good chatbot remains one of the field’s hardest challenges. While chatbots can be used for various tasks, in general they have to understand users’ utterances and provide responses that are relevant to the problem at hand. In the past, methods for constructing chatbot architectures have relied on hand-written rule

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McDonnell, Marian, and David Baxter. "Chatbots and Gender Stereotyping." Interacting with Computers 31, no. 2 (2019): 116–21. http://dx.doi.org/10.1093/iwc/iwz007.

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Abstract Chatbots are very much an emerging technology, and there is still much to learn about how conversational user interfaces will affect the way in which humans communicate not only with computers but also with one another. Further studies on anthropomorphic agents and the projection of human characteristics onto a system are required to further develop this area. Gender stereotypes operate a profound effect on human behaviour. The application of gender to a conversational agent brings along with it the projection of user biases and preconceptions. These feelings and perceptions about an

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Pilato, Giovanni, Agnese Augello, and Salvatore Gaglio. "A Modular System Oriented to the Design of Versatile Knowledge Bases for Chatbots." ISRN Artificial Intelligence 2012 (March 5, 2012): 1–10. http://dx.doi.org/10.5402/2012/363840.

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The paper illustrates a system that implements a framework, which is oriented to the development of a modular knowledge base for a conversational agent. This solution improves the flexibility of intelligent conversational agents in managing conversations. The modularity of the system grants a concurrent and synergic use of different knowledge representation techniques. According to this choice, it is possible to use the most adequate methodology for managing a conversation for a specific domain, taking into account particular features of the dialogue or the user behavior. We illustrate the imp

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Panesar, Kulvinder. "Conversational artificial intelligence - demystifying statistical vs linguistic NLP solutions." Journal of Computer-Assisted Linguistic Research 4, no. 1 (2020): 47. http://dx.doi.org/10.4995/jclr.2020.12932.

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This paper aims to demystify the hype and attention on chatbots and its association with conversational artificial intelligence. Both are slowly emerging as a real presence in our lives from the impressive technological developments in machine learning, deep learning and natural language understanding solutions. However, what is under the hood, and how far and to what extent can chatbots/conversational artificial intelligence solutions work – is our question. Natural language is the most easily understood knowledge representation for people, but certainly not the best for computers because of

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Saniya, Salim Patvegar, Suresh Nandai Shraddha, Deepak Jagtap Prerana, Prakash Patil Pranita, and D. Sawant S. "Online Chatbot Platform for Human Interaction using Python." Journal of Information Technology and Sciences 6, no. 1 (2020): 10–13. https://doi.org/10.5281/zenodo.3741481.

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Now a days, we seen so many types of conversational agents or virtual assistant. Chatbot is a conversational agent which is able to communicate with user. Chatbots are the programs that interact with the clients or user. This technology is started in the 1960, the main aim of this technology is interaction with clients without human interface. The number of chatbot platform are already exists that are text bots. We developed the voice bots based on the concept of machine learning. Thus, this paper describes detailed information of “Online Chatbot Platform for Human Interaction Using Pyth

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Gandhi, Shruti, and Charmy Patel. "Survey: Unconventional Categories of Chatbots that make use of Machine Learning Techniques." September 2023 5, no. 3 (2023): 310–28. http://dx.doi.org/10.36548/jitdw.2023.3.006.

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A growing trend in computer interaction approaches is human-computer interaction, which describes communication between a person and a computer and is known as a chatbot. A conversational agent, often known as a chatbot, is a computer program that attempts to provide responses that appear human during a conversation. Studies on several chatbot applications, are been carried out in this research on the areas of Natural Language Processing (NLP), the Natural Language understanding (NLU), and Intent recognition in recent years. There are several NLU applications in various fields, including Chatb

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Fattepurkar, Prof Gopika, Prathamesh Govekar, Niranjan Khude, Aniket Pore, and Gunjan Gandhi. "A Review on Chatur: Chatbot for College." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 481–86. https://doi.org/10.22214/ijraset.2025.68302.

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Abstract: In today’s fast-paced college environment, students and faculty require timely access to accurate information on a variety of topics, such as admissions, course details, fees, and campus facilities. Traditional methods of information dissemination, such as websites, emails, and in-person consultations, often lead to delays and inefficiencies, causing frustration among users and increasing administrative workloads. To address this challenge, we developed Campus Query: A Q&A Chatbot for College, an intelligent conversational agent designed to provide real-time, accurate answers to

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Tudor Car, Lorainne, Dhakshenya Ardhithy Dhinagaran, Bhone Myint Kyaw, et al. "Conversational Agents in Health Care: Scoping Review and Conceptual Analysis." Journal of Medical Internet Research 22, no. 8 (2020): e17158. http://dx.doi.org/10.2196/17158.

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Background Conversational agents, also known as chatbots, are computer programs designed to simulate human text or verbal conversations. They are increasingly used in a range of fields, including health care. By enabling better accessibility, personalization, and efficiency, conversational agents have the potential to improve patient care. Objective This study aimed to review the current applications, gaps, and challenges in the literature on conversational agents in health care and provide recommendations for their future research, design, and application. Methods We performed a scoping revie

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Aghi, Kushagar. "Chatbot using Zomato API." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 488–93. http://dx.doi.org/10.22214/ijraset.2021.34944.

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Chatbots are program that interact with humans using natural language like English. Computer based chatbots are getting to be distinctly famous as an intuitive and successful open framework between human and machines. They provide conversational output in response, and if commanded, can sometimes also execute tasks. One such bot is being designed in this project, where data about restaurants on the basis of some inputs are collected. Using this data, chatbot is trained to answer the queries. Our project describes the design and development of a conversational agent called Intelligent-Bot. Any

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NSAIF, Wassem Saad, Huda Mohammed SALIH, Hassan Hadi SALEH, and Bashar Talib AL-NUAIM. "Conversational Agents: An Exploration into Chatbot Evolution, Architecture, and Important Techniques." Eurasia Proceedings of Science Technology Engineering and Mathematics 27 (August 15, 2024): 246–62. http://dx.doi.org/10.55549/epstem.1518795.

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A chatbot is a computer software that mimics a user interaction. It is often referred to as a dialogue system or conversational agent. Developers and academics are increasingly focused in designing and implementing Chatbots. This in-depth look focuses on the ever-changing realm of chatbot technology, concentrating on chatbot evolution, architecture, and techniques that drive the most recent breakthroughs. We begin with a brief history and then follow the progress of Chatbots, emphasizing major milestones. The review focuses on the many architectures used in chatbot creation, ranging from class

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Mzwri, Kovan, and Márta TURCSÁNYI-SZABÓ. "Chatbot Development using APIs and Integration into the MOOC." Central-European Journal of New Technologies in Research, Education and Practice 5, no. 1 (2023): 18–30. http://dx.doi.org/10.36427/cejntrep.5.1.5041.

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 In recent years, chatbot technologies have evolved into modern information and communication technology applications that perform many virtual tasks, including learning. One of the challenges in improving the chatbot is the insufficient knowledge base of chatbots, including education-oriented conversational agents, the challenges in connecting the chatbot with course content on Massive Open Online Course platforms. In this study, a chatbot was developed to answer questions using publicly available technologies, specifically Application Program Interfaces (APIs) that promise convenient u

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Martínez-Gárate, Ángel, José Alfonso Aguilar-Calderón, Carolina Tripp-Barba, and Aníbal Zaldívar-Colado. "Enhancing Conversational Agent Development Through a Semi-Automatization Development Proposal." Applied Sciences 15, no. 3 (2025): 1139. https://doi.org/10.3390/app15031139.

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The development of chatbots is often hindered by high costs and time consumption, with existing technologies and frameworks not fully addressing the diverse requirements for creating robust conversational agents across platforms like WhatsApp. This is a limitation for the implementation of these frameworks in a professional environment, thus representing both opportunities and complexities. This article presents improvements to the Xatkit framework, utilizing Model-Driven Development techniques to simplify chatbot development and extend support for WhatsApp. Additionally, the integration of th

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Nagargoje, Prof Vivek. "J.A.R.V.I.S Organizational Virtual Assistant." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 4664–67. http://dx.doi.org/10.22214/ijraset.2021.35066.

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Chatbots, or conversational interfaces as they are also known, present a new way for individuals to interact with computer systems. Traditionally, to get a question answered by a software program involved using a search engine, or filling out a form. A chatbot allows a user to simply ask questions in the same manner that they would address a human. The most well known chatbots currently are voice chatbots: Alexa and Siri. However, chatbots are currently being adopted at a high rate on computer chat platforms. The technology at the core of the rise of the chatbot is natural language processing

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Schachner, Theresa, Roman Keller, and Florian v Wangenheim. "Artificial Intelligence-Based Conversational Agents for Chronic Conditions: Systematic Literature Review." Journal of Medical Internet Research 22, no. 9 (2020): e20701. http://dx.doi.org/10.2196/20701.

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Background A rising number of conversational agents or chatbots are equipped with artificial intelligence (AI) architecture. They are increasingly prevalent in health care applications such as those providing education and support to patients with chronic diseases, one of the leading causes of death in the 21st century. AI-based chatbots enable more effective and frequent interactions with such patients. Objective The goal of this systematic literature review is to review the characteristics, health care conditions, and AI architectures of AI-based conversational agents designed specifically f

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Raj, Kanak, Kaushik Roy, Vamshi Bonagiri, et al. "K-PERM: Personalized Response Generation Using Dynamic Knowledge Retrieval and Persona-Adaptive Queries." Proceedings of the AAAI Symposium Series 3, no. 1 (2024): 219–26. http://dx.doi.org/10.1609/aaaiss.v3i1.31203.

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Personalizing conversational agents can enhance the quality of conversations and increase user engagement. However, they often lack external knowledge to appropriately tend to a user’s persona. This is crucial for practical applications like mental health support, nutrition planning, culturally sensitive conversations, or reducing toxic behavior in conversational agents. To enhance the relevance and comprehensiveness of personalized responses, we propose using a two-step approach that involves (1) selectively integrating user personas and (2) contextualizing the response by supplementing infor

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Vadlamani, Srikanth, and Daksha Borada. "The Role of LLM Agent Apps in Conversational AI." International Journal of Research in Modern Engineering & Emerging Technology 13, no. 4 (2025): 205–23. https://doi.org/10.63345/ijrmeet.org.v13.i4.12.

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The rapid growth of Large Language Models (LLMs) has tremendously boosted the strength of conversational artificial intelligence applications. In this regard, LLM agent applications have become strong tools for automating and individualizing conversations across industries such as customer service, healthcare, education, and entertainment. LLM agent applications use LLMs to have sophisticated, contextually aware conversations, thereby providing users with a natural conversational experience. Though they have great capabilities, there is a massive research gap regarding the distinctive roles an

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Moulya, S., and T. R. Pragathi. "Mental Health Assist and Diagnosis Conversational Interface using Logistic Regression Model for Emotion and Sentiment Analysis." Journal of Physics: Conference Series 2161, no. 1 (2022): 012039. http://dx.doi.org/10.1088/1742-6596/2161/1/012039.

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Abstract The aim of this work was to create a fully functional AI-ML based conversational agent that behaves like a real time therapist which analyses the user’s emotion at every step and provides appropriate responses and feedback. AI chatbots, although fairly new to the domain of mental health, can help in destigmatizing seeking help, and are more easily accessible to everyone, at any time. Chatbots provide an effective way to communicate with a user and offer helpful emotional support in a more economical way. While making regular psychiatric visits often require a fixed duration/appointmen

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Mahesh, Vanjani, Aiken Milam, and Park Mina. "Chatbots for Multilingual Conversations." Journal of Management Science and Business Intelligence 4, no. 1 (2019): 19–24. https://doi.org/10.5281/zenodo.3264011.

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Chatbots emulate human dialogue to provide a more intuitive user interface to applications or simply provide entertainment. Chatbots rely on technology to function and new and emerging technologies such as NLP (Natural Language Processing) and AI (Artificial Intelligence) can be used to increase the ability of chatbots to emulate a more natural and free flowing conversation. As more and more mobile device users transition to increased use of texts and messaging chatbots can be used to provide consumers with multilingual support and services. While some chatbots have been developed in other lan

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Relieu, Marc. "How Lenny the bot convinces you that he is a person: Storytelling, affiliations, and alignments in multi-unit turns." Discourse & Communication 18, no. 6 (2024): 882–91. http://dx.doi.org/10.1177/17504813241271437.

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This research delves into the world of conversation analysis, focusing on the unique conversational agent, Lenny. In contrast to most modern AI-based chatbots, Lenny employs a minimalistic approach, utilizing pre-recorded turns to engage with unsolicited callers and extend interactions. The study aims to dissect how Lenny’s long turns contribute to displaying ‘his’ personhood. By analyzing Lenny’s long turn in interaction, we uncover how it consolidates Lenny’s relatable character. Through analysis of a corpus of recorded interactions, the paper highlights the role of turn design in simulating

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Mathewson, Kory, and Piotr Mirowski. "Improvised Theatre Alongside Artificial Intelligences." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 13, no. 1 (2021): 66–72. http://dx.doi.org/10.1609/aiide.v13i1.12926.

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This study presents the first report of Artificial Improvisation, or improvisational theatre performed live, on-stage, alongside an artificial intelligence-based improvisational performer. The Artificial Improvisor is a form of artificial conversational agent, or chatbot, focused on open domain dialogue and collaborative narrative generation. Using state-of-the-art machine learning techniques spanning from natural language processing and speech recognition to reinforcement and deep learning, these chatbots have become more lifelike and harder to discern from humans. Recent work in conversation

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Cheng, Sheung-Tak, Peter Ng, and Tomoko Wakui. "ACCEPTABILITY OF A CHATBOT FOR INFORMATION AND ADVICE ON DEMENTIA CAREGIVING." Innovation in Aging 8, Supplement_1 (2024): 1285. https://doi.org/10.1093/geroni/igae098.4107.

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Abstract Providing ongoing support to caregivers as their needs change in the long-term course of dementia is a serious challenge to any healthcare system. Conversational artificial intelligence (AI) operating 24/7 may help to tackle this problem. This presentation describes the development of a generative AI chatbot (called Chatbot-A) using the GPT-4o large language model, with a personality agent to constrain its behavior to providing advice on dementia caregiving based on a revised version of the Benefit-Finding Intervention manual (an intervention reported in JG:PS and other journals). The

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Bin Sawad, Abdullah, Bhuva Narayan, Ahlam Alnefaie, et al. "A Systematic Review on Healthcare Artificial Intelligent Conversational Agents for Chronic Conditions." Sensors 22, no. 7 (2022): 2625. http://dx.doi.org/10.3390/s22072625.

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This paper reviews different types of conversational agents used in health care for chronic conditions, examining their underlying communication technology, evaluation measures, and AI methods. A systematic search was performed in February 2021 on PubMed Medline, EMBASE, PsycINFO, CINAHL, Web of Science, and ACM Digital Library. Studies were included if they focused on consumers, caregivers, or healthcare professionals in the prevention, treatment, or rehabilitation of chronic diseases, involved conversational agents, and tested the system with human users. The search retrieved 1087 articles.

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Calvaresi, Davide, Jean-Paul Calbimonte, Enrico Siboni, et al. "EREBOTS: Privacy-Compliant Agent-Based Platform for Multi-Scenario Personalized Health-Assistant Chatbots." Electronics 10, no. 6 (2021): 666. http://dx.doi.org/10.3390/electronics10060666.

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Context. Asynchronous messaging is increasingly used to support human–machine interactions, generally implemented through chatbots. Such virtual entities assist the users in activities of different kinds (e.g., work, leisure, and health-related) and are becoming ingrained into humans’ habits due to factors including (i) the availability of mobile devices such as smartphones and tablets, (ii) the increasingly engaging nature of chatbot interactions, (iii) the release of dedicated APIs from messaging platforms, and (iv) increasingly complex AI-based mechanisms to power the bots’ behaviors. Never

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Villa, Laura, David Carneros-Prado, Cosmin C. Dobrescu, Adrián Sánchez-Miguel, Guillermo Cubero, and Ramón Hervás. "Comparative Analysis of Generic and Fine-Tuned Large Language Models for Conversational Agent Systems." Robotics 13, no. 5 (2024): 68. http://dx.doi.org/10.3390/robotics13050068.

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In the rapidly evolving domain of conversational agents, the integration of Large Language Models (LLMs) into Chatbot Development Platforms (CDPs) is a significant innovation. This study compares the efficacy of employing generic and fine-tuned GPT-3.5-turbo models for designing dialog flows, focusing on the intent and entity recognition crucial for dynamic conversational interactions. Two distinct approaches are introduced: a generic GPT-based system (G-GPT) leveraging the pre-trained model with complex prompts for intent and entity detection, and a fine-tuned GPT-based system (FT-GPT) employ

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Pérez, Anxo, Paula Lopez-Otero, and Javier Parapar. "Designing an Open Source Virtual Assistant." Proceedings 54, no. 1 (2020): 30. http://dx.doi.org/10.3390/proceedings2020054030.

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A chatbot is a type of agent that allows people to interact with an information repository using natural language. Nowadays, chatbots have been incorporated in the form of conversational assistants on the most important mobile and desktop platforms. In this article, we present our design of an assistant developed with open-source and widely used components. Our proposal covers the process end-to-end, from information gathering and processing to visual and speech-based interaction. We have deployed a proof of concept over the website of our Computer Science Faculty.

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Young Oh, Eun, Donggil Song, and Hyeonmi Hong. "Interactive Computing Technology in Anti-Bullying Education: The Effects of Conversation-Bot’s Role on K-12 Students’ Attitude Change Toward Bullying Problems." Journal of Educational Computing Research 58, no. 1 (2019): 200–219. http://dx.doi.org/10.1177/0735633119839177.

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The aim of this study was to examine the effects of an anti-bullying activity that utilizes conversational virtual agents (called conversation-bots or chatbots) on students’ attitudes toward bullying problems. An experimental pre- or posttest design with a three-group setting was used. Eighty-nine fifth-grade students were assigned to one of three groups: Conversation with a virtual agent of (a) bully’s role, (b) victim’s role, and (c) teacher’s role. All agents are conversation-bots designed to support learner–computer interactions. The bully agent defends the notion that bullying behaviors a

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Isinkaye, Folasade Olubusola, Imran Gbolahan AbiodunBabs, and Michael Tobi Paul. "Development of a Mobile-Based Hostel Location and Recommendation Chatbot System." International Journal of Information Technology and Computer Science 14, no. 3 (2022): 23–33. http://dx.doi.org/10.5815/ijitcs.2022.03.03.

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A Chabot is a conversational intelligent agent that has the capability of engaging in human-like interaction with its users. A lot of chatbots have been developed, but to the best of our knowledge, there are few or no chatbots that have been developed for hostel location integrated with a recommendation component to ease the cost, time, and stress of identifying suitable hostels for students, especially at higher institutions of learning. Therefore, this work develops a location-based chatbot system enhanced with recommendation capabilities to allow students to locate hostels that satisfy thei

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Septiyanti, Nisa Dwi, Muhammad Irfan Luthfi, and Darmawansah Darmawansah. "Effect of Chatbot-Assisted Learning on Students’ Learning Motivation and Its Pedagogical Approaches." Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika 10, no. 1 (2024): 69–77. http://dx.doi.org/10.23917/khif.v10i1.4246.

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Abstract- The use of chatbots in the learning process has been increasingly investigated and applied. While many studies have discussed the chatbot's ability to motivate students' interest in learning, few have examined whether students' perception of learning affects the effectiveness of chatbots and the pedagogical approach taken by chatbots as conversational agents during the learning process. There is a need for new analysis to capture the effects of Chatbot-Assisted Learning (Chatbot-AL) and student-chatbot conversations. In an eight-week semester, 48 first-year undergraduate students par

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Gaffney, Hannah, Warren Mansell, and Sara Tai. "Conversational Agents in the Treatment of Mental Health Problems: Mixed-Method Systematic Review." JMIR Mental Health 6, no. 10 (2019): e14166. http://dx.doi.org/10.2196/14166.

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Background The use of conversational agent interventions (including chatbots and robots) in mental health is growing at a fast pace. Recent existing reviews have focused exclusively on a subset of embodied conversational agent interventions despite other modalities aiming to achieve the common goal of improved mental health. Objective This study aimed to review the use of conversational agent interventions in the treatment of mental health problems. Methods We performed a systematic search using relevant databases (MEDLINE, EMBASE, PsycINFO, Web of Science, and Cochrane library). Studies that

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Garzón-Quiroz, Mao, Guillermo Del Campo-Saltos, and Beatriz Loor-Ávila. "Análisis sistemático sobre la eficiencia comunicativa entre chatbots basados en reglas y modelos de lenguaje natural." Universitas, no. 42 (February 28, 2025): 167–92. https://doi.org/10.17163/uni.n42.2025.07.

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The study was grounded in a systematic literature review on the communicative efficiencies of rule-based conversational agents and those powered by natural language models with artificial intelligence. A total of 175 documents were analyzed as the basis for this review. Additionally, a historical analysis of the first recorded conversational agent, ELIZA, developed in 1966, was included, highlighting its pivotalrole in the emergence of rule-based systems. The study also delved into the arguments underpinning thesignificant differences between rule-based conversational agents and those leveragi

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Arnis, Amelia, Yeni Rustina, Allenidekania Allenidekania, and Fariz Darari. "The role of chatbots in paediatric chronic disease management: Trends, findings, and future recommendations." Malahayati International Journal of Nursing and Health Science 7, no. 10 (2024): 1227–35. https://doi.org/10.33024/minh.v7i10.564.

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Background: Chronic diseases in children, such as chronic kidney disease (CKD), diabetes, and asthma require complex long-term management because they can affect the quality of life physically, psychologically, socially, and educationally. One of the new innovations in supporting the management of chronic diseases in children is the use of chatbots that play a role in education, health monitoring, and psychological support. Purpose: To review the literature on the effectiveness of chatbots in supporting self-care in children with chronic diseases. Method: This literature review study examined

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Benabdeouahed, Redouane, and Yassine Elkhatibi. "Confirmatory Exploration of innovation in virtual exchanges through a study on Virtual Agents." International Journal of Automation and Digital Transformation 3, no. 1 (2024): 65–85. http://dx.doi.org/10.54878/2vpnn535.

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The use of Conversational Agents for consumer services continues to grow, and the service industry is no exception. Carried out among 340 Moroccan consumers, this study shows the importance of perceived anthropomorphism, social presence, perceived trust, social influence, perceived cost, and facilitating conditions of a conversational agent in increasing adoption intention using the UTAUT model. The expected effort had no effect. This research confirms the moderating role of age on the relationship between social influence and intention to use, while gender and level of education had no modera

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Moore, Robert J., Sungeun An, and Olivia H. Marrese. "Understanding is a Two-Way Street: User-Initiated Repair on Agent Responses and Hearing in Conversational Interfaces." Proceedings of the ACM on Human-Computer Interaction 8, CSCW1 (2024): 1–26. http://dx.doi.org/10.1145/3641026.

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Although methods for repairing prior turns in natural conversation are critical for enabling mutual understanding, or successful communication, these methods are seldom built into conversational user interfaces systematically. Chatbots and voice assistants tend to ask users to paraphrase what they said if it was not understood, but users cannot do the same if they encounter trouble in understanding what the agent said. Understanding is a one-way street in most (intent-based) conversation-like interfaces. An exception to this is Moore and Arar (2019), who demonstrate nine types of user-initiate

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Mendoza, Sonia, Luis Martín Sánchez-Adame, José Fidel Urquiza-Yllescas, Beatriz A. González-Beltrán, and Dominique Decouchant. "A Model to Develop Chatbots for Assisting the Teaching and Learning Process." Sensors 22, no. 15 (2022): 5532. http://dx.doi.org/10.3390/s22155532.

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Recently, in the commercial and entertainment sectors, we have seen increasing interest in incorporating chatbots into websites and apps, in order to assist customers and clients. In the academic area, chatbots are useful to provide some guidance and information about courses, admission processes and procedures, study programs, and scholarly services. However, these virtual assistants have limited mechanisms to suitably help the teaching and learning process, considering that these mechanisms should be advantageous for all the people involved. In this article, we design a model for developing

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Srikong, Mathuwan, Panita Wannapiroon, and Prachyanun Nilsook. "Crystallized Intelligence Wisdom Repository Management System with a Conversational Agent." International Education Studies 16, no. 2 (2023): 150. http://dx.doi.org/10.5539/ies.v16n2p150.

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This research was undertaken by synthesizing theories, documents, textbooks, research articles, and related academic articles relating to the wisdom repository management process. The objective is to present a system architecture and develop a knowledge management system which culminates in a repository of crystallized intelligence with a conversational agent that can promote learning for medical students by introducing a system architecture to develop intelligent agent technology. Through mobile technology, accessible anytime, anywhere, lifelong learning for medical students will be supported

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Permadi, Iwan. "Criteria Selection and Comparative Analysis of Popular Chatbot Frameworks (Dialog flow, Microsoft Bot Framework, IBM Watson Assistant and Rasa) For Implementation in Libraries: a Systematic Literature Review." JPUA: Jurnal Perpustakaan Universitas Airlangga: Media Informasi dan Komunikasi Kepustakawanan 13, no. 2 (2023): 94–103. http://dx.doi.org/10.20473/jpua.v13i2.2023.94-103.

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ABSTRACT Chatbots are increasingly popular in various fields, including in libraries, to improve services and interactions with users. In choosing a chatbot for libraries, proper criteria are needed. Some common chatbot frameworks are Dialogflow, Microsoft Bot Framework, IBM Watson Assistant, and Rasa, which have advantages and disadvantages in the library context. This research conducts a systematic literature review on the selection criteria and comparison of popular chatbot frameworks such as Dialogflow, Microsoft Bot Framework, IBM Watson Assistant, and Rasa in library implementation. The

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Niranjana, Dr G. "A Review on Healthcare Services Using Dual Chatbots as Conversational Agents." International Journal for Research in Applied Science and Engineering Technology 10, no. 1 (2022): 1295–300. http://dx.doi.org/10.22214/ijraset.2022.40014.

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Abstract: A chat bot is an AI tool that interprets information provided by humans and responds accordingly. It is used to carry out tasks like mimic human behavior. Many of the chat bot conversations between humans and machines are repetitive. Instead of just talking to one another, a chat bot can communicate with the outside world by analyzing the user's needs and actions. Having a chat bot assistant that can help users complete their tasks makes them feel like they're doing something right. It eliminates the user's need to do the work for them. This idea has been proposed to introduce a dual

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Aina, Modupe Aduke, Mary Ayodeji Gbenga-Epebinu, Rebecca Oluwafunke Olofinbiyi, Oluwakemi Christie Ogidan, and Tosin O. Ayedun. "Perception and Acceptance of Medical Chatbot Among Undergraduates in Ekiti State University, Nigeria." British Journal of Education 11, no. 11 (2023): 1–14. http://dx.doi.org/10.37745/bje.2013/vol11n11114.

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This study explores the perceptions and acceptance of medical chatbots among undergraduate students at Ekiti State University, Ado-Ekiti, Nigeria. A medical chatbot is an artificially intelligent conversational agent that simulates human-like communication, catering to user inquiries and generating logical responses. These chatbots leverage natural language processing and machine learning to engage in dynamic interactions, retrieve relevant information, and adapt to new data. This research investigates two primary aspects: the perception of undergraduate students towards the use of medical cha

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Titova, Svetlana V., and Kristina T. Temuryan. "Intelligent agents in teaching foreign languages: typology, opportunities, challenges." Yazyk i kul'tura, no. 65 (2024): 262–87. https://doi.org/10.17223/19996195/65/12.

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Since artificial intelligence first appeared in the 1950s, the interest towards it has been changing throughout its existence, but in a number of countries, including Russia, there is currently an increase in the government’s interest in artificial intelligence technologies that have found application in various fields, such as finance, medicine and education. The use of artificial intelligence in teaching executes functions such as, for instance, natural language generation, personalisation of learning and proctoring. At the same time, besides the organisation of the educational process or th

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