Open lucasschepers opened 6 months ago
Have some sort of demo where a book can be inputed and one (or several) models can recommend similar books based on user reviews. Techniques to be used may inculde collaborative filtering based on correlation coefficients, distances or cosine similarities. the best book may be found based on the (k-)nearest neighbours.
Because I don't know enough about unsupervised learning, I do not know how to evaluate the model with some sort of model performance. This needs be carefully considered before more advanced algorithms can be considered.
https://www.kaggle.com/code/yldzburhan/books-collaborative-filtering
https://www.kaggle.com/datasets/zygmunt/goodbooks-10k/data?select=tags.csv
https://www.kaggle.com/datasets/jealousleopard/goodreadsbooks/data
https://www.kaggle.com/code/hoshi7/goodreads-analysis-and-recommending-books
https://www.kaggle.com/code/sriharshavogeti/collaborative-recommender-system-on-goodreads
https://www.kaggle.com/code/omarzaghlol/goodreads-2-book-recommender-system