GitHub / coderjolly / news-recommender
This is a news recommender system that uses beautiful-soup to scrape news articles, their categories and descriptions to create a data dump. It then uses word embedding techniques such tf-idf, word2vec for content based news recommendation and LightRF, LightFM to explore hybrid and collaborative filtering based recommender models.
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/coderjolly%2Fnews-recommender
Stars: 1
Forks: 1
Open issues: 0
License: gpl-3.0
Language: Jupyter Notebook
Size: 1.48 MB
Dependencies parsed at: Pending
Created at: about 2 years ago
Updated at: 7 months ago
Pushed at: almost 2 years ago
Last synced at: about 1 month ago
Topics: collaborative-filtering, lightrf, nlp-machine-learning, nltk-python, recommendation-system, recommender-system, tf-idf-vectorizer