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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: June 2026
Volume 11 | Issue 6
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 121
Article Submitted : 24730
Article Published : 9361
Total Authors : 24875
Total Reviewer : 861
Total Countries : 169
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| Paper Title: | Intelligent Course Recommender Portal for University Students Using Hybrid Collaborative Filtering |
| Authors Name: | D.JAYA SONIYA , NALATHOTI SAI HARSHITHA , MYLA VENKATA SOWJANYA , KOTHURI VASAVI , DOVA ARCHANA |
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IJRTI_212443
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| Published Paper Id: | IJRTI2605078 |
| Published In: | Volume 11 Issue 5, May-2026 |
| DOI: | |
| Abstract: | Selecting appropriate courses is a critical decision for university students, as it directly influences their academic performance and future career opportunities. Traditional course selection methods largely depend on informal guidance from peers or instructors, which may not provide accurate or personalized recommendations. To address this challenge, the present work proposes an Intelligent Course Recommender Portal that employs machine learning techniques to generate data-driven, personalized course suggestions. The system analyses historical academic data, including student grades and course enrolment patterns, to identify similarities and predict suitable courses. A hybrid collaborative filtering approach is implemented by combining user-based and item-based methods with an autoencoder-based model to capture complex non-linear patterns and improve prediction accuracy. Performance is evaluated using Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The system is developed as a web-based application using Streamlit, providing an interactive interface for real-time recommendations along with predicted performance indicators. The results demonstrate that the proposed system improves the accuracy and reliability of course recommendations, thereby assisting students in making informed academic decisions. |
| Keywords: | Course Recommendation System, Collaborative Filtering, Autoencoder, Hybrid Filtering, Machine Learning, Streamlit, MAE, RMSE, Personalized Learning. |
| Cite Article: | "Intelligent Course Recommender Portal for University Students Using Hybrid Collaborative Filtering", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 5, page no.a648-a653, May-2026, Available :http://www.ijrti.org/papers/IJRTI2605078.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2605078
Registration ID:212443
Published In: Volume 11 Issue 5, May-2026
DOI (Digital Object Identifier):
Page No: a648-a653 Country: HYDERABAD, Telangana, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2605078 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2605078 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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