Artificial Neural Network Based University Chatbot System

Bhartiya, Namrata; Jangid, Namrata; Jannu, Sheetal; Shukla, Purvika; Chapaneri, Radhika

doi:10.1109/ibssc47189.2019.8973095

Cited by 20 publications

(9 citation statements)

References 4 publications

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“…This optimizes the usage of human and financial resources while enhancing user engagement. [13] The purpose of this project is to construct an autonomous education system that can answer to user requests with full information. Unlike earlier chatbots that were exclusively based on local databases, our solution includes both local and internet databases for optimum engagement, scalability, and userfriendliness.…”

Section: Literarure Reviewmentioning

confidence: 99%

Campus Companion : Creating a Supportive Chat – Assistant for Students

Bodapati

2024

IJSREM

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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 replies that fit with them. Natural language processing technologies, including voice recognition, natural language interpretation, and natural language production, will be used to foster natural discussions. A number of machine learning approaches, such as transformers, attention processes, and recurrent neural networks, will be investigated in order to classify intent and deliver replies. The objective is to construct a powerful and versatile chatbot that can grasp arguments in their context, preserve the debate's status, and answer in a manner that sounds human. Assessment criteria such as accuracy, recall, and precision will be utilized to develop and adapt the chatbot. Numerous businesses, including education, entertainment, customer service, and other disciplines, may profit from the employment of this chatbot. The implementation of intelligent conversational interfaces on websites has the potential to greatly enhance user experience. Keywords— Chatbot, Flask, MySQL, TensorFlow, Keras, Website Interaction, Natural Language Processing (NLP), Conversational AI, Intent Classification, Response Generation, Machine Learning Models, Recurrent Neural Networks (RNNs), Transformer Models, Attention Mechanisms, User Experience (UX), Contextual Conversations, Dialogue State Management, Human-like Responses, Customer Service Automation, Educational Chatbot, Entertainment Applications.

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Section: Literarure Reviewmentioning

confidence: 99%

Campus Companion : Creating a Supportive Chat – Assistant for Students

Bodapati

2024

IJSREM

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“…Examples of web services are: RASA (Jiao, 2020), DialogFlow (Muhammad et al, 2020), (Ruane et al, 2020), etc. and neural networks (Bhartiya et al, 2019). The ADA project uses artificial intelligence-based approaches, i.e.…”

Section: Techniques and Technologies Used For Project Developmentmentioning

confidence: 99%

An Example of Chatbot in the Field of Education in the Republic of Serbia

Vukomanović¹,

Deretić²,

Kabiljo³

et al. 2022

Jour Proc Manag New Tech

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Students can retrieve information from the website or use the services of an existing information system (provided the information system is on the internet). However, we know from experience that searching a website is time-consuming or even inaccurate, and the functionality of the information system is limited. Chatbot makes it more natural, efficient and faster. Chatbot can understand natural language, i.e. written text and voice messages. It gives precise answers and performs all actions intended by the website and / or the information system. But the website and the information system do not have the richness of language that the chatbot has. You have to log in to the information system and know how to use it, and each new version requires new learning. If you know how Viber or FB Messenger work, you probably know how to use chatbot. The services provided by chatbot are visible on communication platforms used by a large number of users, and thus the quality of these services is better. Due to the use of chats, the human resources of the educational institution are redirected/retrained to more responsible and creative jobs because the workload has been relieved. The paper presents a chatbot called ADA, developed at the Belgrade Business and Arts Academy of Applied Studies (BAPUSS), and shows basic usage statistics. It also points out the importance of chatbots as a communication channel in educational institutions.

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“…In this study, [9] described the design and implementation of a university counseling chatbot that provided answers to queries related to the field of Engineering. It covered a range of applications, including queries relating to admission to the university, available courses, job placement, and many more.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This will allow for availability to users from all around the world to easily access the system. Lastly, this study implemented speech-to-text functionality, similar to [9] listed above. However, this API slowed down response times and on occasion would crash after overuse.…”

Section: Literature Reviewmentioning

confidence: 99%