In this project, I have implemented a content-based book recommendation system. The user can introduce a title or a description of a book he likes, and the k number of recommendations he wants to get. The system will return the k books whose summaries are the most simmilar to the one of the book introduced by the user (using the cosine simmilarity of the summaries' embeddings).
pip install git+https://github.com/leyresv/Book_Recommendation_System.git
pip install -r requirements.txt
Before using the recommendation system, you need to download and process the CMU Book Summaries Dataset. To do it, open a terminal prompt on the root directory and introduce the following command:
python data/utils.py
The data will take a few minutes to be ready. Once it's done, you can use the recommendation system by simply introducing the following command:
python main/main.py
If you prefer using the user interface, introduce the following command from the root directory:
python main/gui.py
Book_recommendation.mp4
(To be implemented: same author search)