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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM28616
Volume:
8 |
2 |
Feb 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
By harnessing the capabilities of Large Language Models (LLM), the proposed system evolves into a sophisticated conversational agent, capable of understanding nuanced user inputs, providing context-aware responses, and delivering an unparalleled level of engagement. This chatbot is also equipped to assess a student’s likelihood of being accepted into a specific program at the college using a machine learning (ML) model. The model analyzes the student’s rank and eligible quota (such as reserved categories) in conjunction with historical admission data to gauge their chances of acceptance. It also recommends alternative programs where the student may have a better chance of admission based on their rank. The chatbot also features a smart Applicant Tracking System (ATS) that assists students in evaluating their resumes. This system provides
KEYWORDS
Publication Date
12/31/45594
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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