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A Study on the Development of a College Inquiry Chatbot System

  • Unique Paper ID: 169462
  • Volume: 11
  • Issue: 6
  • PageNo: 1065-1067
  • Abstract:
  • This paper examines the design and deployment of an advanced college inquiry chatbot system utilizing machine learning models such as Support Vector Machines (SVM), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), and BERT, all of which are crucial for the system's success in providing real-time, precise answers to students' questions. The paper highlights the integration of these models with data preprocessing techniques to enhance the accuracy and context-awareness of responses. A detailed analysis is provided on the strengths and weaknesses of each model, focusing on their suitability for different types of queries in educational environments. This work aims to provide guidelines for developing AI-powered systems that not only automate processes but also personalize student interactions, improving overall user satisfaction.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 6
  • PageNo: 1065-1067

A Study on the Development of a College Inquiry Chatbot System

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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