OKEKE, DAVID CHIBUEZE (2025) AN E-LIBRARY RECOMMENDER SYSTEM FOR COMPUTER SCIENCE STUDENTS USING CONTENT-BASED FILTERING TECHNIQUE. Other thesis, GODFREY OKOYE UNIVERSITY, ENUGU.
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Abstract
The project involved implementing a Book Recommender System with the Django framework and using Machine Learning techniques. The primary purpose of this system was to assist users in locating books that are related to one another in some manner using the book title, author, and description. This system was integrated into a Django web application where users can browse through the catalogue of books, which displays each book's title, author, description and a cover image. The most significant part of the system is a recommendation engine which, based on the book content the user is currently viewing, suggests new books that are not rated or based on any prior history of the user. For such purposes, the system employs a technique called TF-IDF (Term Frequency - Inverse Document Frequency), which transforms the book text into numerical form depicting how important a word is. Then, it uses something called cosine similarity to compute how like the books are to one another, looking at the patterns of words used in the books. A special method was designed which excludes the book that is being viewed from the top recommended books to be returned. However, for the web interface, Django was used; Scikit-learn was used for the machine learning part; and SQLite was used as the database. This system is straightforward and effective for students, instructors, or any individuals searching for books relevant to what they need.
| Item Type: | Thesis (Other) |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Civil Engineering and the Environment |
| Depositing User: | Uchenna Eneogwe |
| Date Deposited: | 03 Jul 2026 12:15 |
| Last Modified: | 03 Jul 2026 12:15 |
| URI: | http://eprints.gouni.edu.ng/id/eprint/5871 |
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