https://github.com/aungkaungpyaepaing/book-recommendation-system

Book recommendation system using user base collaborative filter method and testing the accuracy result with different algorithm
https://github.com/aungkaungpyaepaing/book-recommendation-system

accuracy-testing bookrecommendsystem collaborative-filtering pearson-correlation recommendation-system user-based-recommendation

Last synced: about 2 months ago
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Book recommendation system using user base collaborative filter method and testing the accuracy result with different algorithm

• Host: GitHub
• URL: https://github.com/aungkaungpyaepaing/book-recommendation-system
• Owner: aungkaungpyaepaing
• Created: 2023-10-09T17:28:31.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-10-09T17:44:28.000Z (about 1 year ago)
• Last Synced: 2023-10-09T18:39:59.914Z (about 1 year ago)
• Topics: accuracy-testing, bookrecommendsystem, collaborative-filtering, pearson-correlation, recommendation-system, user-based-recommendation
• Language: Jupyter Notebook
• Homepage:
• Size: 331 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Book-Recommendation-System

A recommendation system has been developed and it has been addressing the issue of selecting the products for the users depending on the user's interests and tastes. This project studies two specific recommendation algorithms, named User-based Collaborative filtering algorithm and FunkSVD. 

This study aimed to develop a book recommendation system and compare the two algorithms according to their accuracy rating. 

The tests’ results indicated that the User-based collaborative filtering algorithm may be more accurate than the FunkSVD but further research is required to come to a concrete conclusion.

As a reference dataset, the Book Recommendation Dataset from Kaggle uploaded by MÖBIUS was used.

Link->https://www.kaggle.com/datasets/arashnic/book-recommendation-dataset

# BOOK RECOMMENDATION SYSTEM TESTING



# ALGORITHM COMPARISON



#NOTE

In this project- accuracy testing has been done with different methods including Pearson Correlation and RMSE. Further improvements might be required but feel free to take reference if anything is needed.