StumbleUpon is a user-curated web content discovery engine that recommends relevant, high quality pages and media to its users, based on their interests. While some pages we recommend, such as news articles or seasonal recipes, are only relevant for a short period of time, others maintain a timeless quality and can be recommended to users long after they are discovered. In other words, pages can either be classified as "ephemeral" or "evergreen". The ratings we get from our community give us strong signals that a page may no longer be relevant - but what if we could make this distinction ahead of time? A high quality prediction of "ephemeral" or "evergreen" would greatly improve a recommendation system like ours.
gun-py / stumbleupon-averaging-ensemble Goto Github PK
View Code? Open in Web Editor NEWClassifier to categorize webpages as evergreen or non-evergreen using an averaging ensemble of BERT, Tree Based and Traditional Models
License: Apache License 2.0