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DC Field | Value | Language |
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dc.contributor.author | Ramalakshmi, Krishnamurthy | - |
dc.contributor.author | David, David Jasmine | - |
dc.contributor.author | Selvarathi, Mariappan | - |
dc.contributor.author | Jebaseeli, Theena Jemima | - |
dc.date.accessioned | 2024-04-08T04:11:10Z | - |
dc.date.available | 2024-04-08T04:11:10Z | - |
dc.date.issued | 2023 | - |
dc.identifier.citation | Vol. 59, No. 1 | en_US |
dc.identifier.issn | 2673-4591 | - |
dc.identifier.uri | https://doi.org/10.3390/engproc2023059016 | - |
dc.identifier.uri | http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/15101 | - |
dc.description.abstract | A chatbot is a computer program that uses general rules and Artificial Intelligence techniques to simulate human conversation. This paper highlights the different scenarios of human-computer interaction and the journey it has gone through from evolution to evolvement to innovation to the development of the technical era. Here, the main focus is on the ways humans interact with the computer and how it has changed day-to-day life and reduced human efforts in performing everyday activities. There is an impact of HCI (Human–Computer Interaction) on people and has consequences in the form of both advantages and disadvantages of this interaction. The various innovations and machines have given birth to human–computer interaction as well as technology interaction. The main objective is to style the interface amongst men as well with Personal Computers (PCs) as usual as the interface amid beings. The user can interact in this system using text or voice. As per way as interaction is concerned direct, indirect, and strategic interaction of humans with computers and the latest gadgets is possible. Dynamic intelligence makes it like real-time communication with an individual. It can handle the user request and offer relevant information that can be used as a friend one would seek for knowledge. The proposed system is developed using the Rasa of an open-source platform. Further, the article focuses on the features and role of chatbots in an educational context. High precision in sentence analysis is attained with the aid of the proposed method up to a 91% hit ratio. The hit rate for the similarity computation is high. The system can handle a broader variety of requests as a consequence of its ability to recognize many ways to phrase the same inquiry and map them to related results. © 2023 by the authors. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Engineering Proceedings | en_US |
dc.publisher | Multidisciplinary Digital Publishing Institute (MDPI) | en_US |
dc.subject | Chatbot | en_US |
dc.subject | Communication | en_US |
dc.subject | Human–Computer Interaction | en_US |
dc.subject | Lstm | en_US |
dc.subject | Natural Language Understanding | en_US |
dc.subject | Rasa | en_US |
dc.subject | Rnn | en_US |
dc.subject | Web Scrapping | en_US |
dc.title | Using Artificial Intelligence Methods to Create A Chatbot for University Questions and Answers † | en_US |
dc.type | Article | en_US |
Appears in Collections: | Journal Articles |
Files in This Item:
File | Size | Format | |
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engproc-59-00016.pdf | 937.42 kB | Adobe PDF | View/Open |
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