Recommender IBMWS package is a Python Package to recommend articles for users of the IBM Watson Studio platform.
This Recommender uses a hybrid approach of Content-Based Filtering and Collaborative Filtering to make recommendations.
The content base recommendation system developed relies on a user profile, text vectorization, similarity calculation, ranking and recommendation, as well as handling of new users to deal with the cold start problem.
Import the Recommender
from recommender_ibmws.recommender import Recommender
rec = Recommender()
Load data
rec.load_data(inter_path='user-item-interactions.csv', content_path='articles_community.csv')
Make recomendations
rec.make_content_recs(user_id=8, m=10)
Find number of users
rec.n_users