akirasosa/nrms-bert

Neural News Recommendation with Multi-Head Self-Attention using BERT

32
/ 100
Emerging

This helps news organizations and media platforms improve their article recommendation systems. It takes a collection of news articles and user reading histories to generate personalized news recommendations for individual users. Content strategists, data scientists, and product managers at news publishers would use this to enhance user engagement.

No commits in the last 6 months.

Use this if you need a baseline recommendation engine to suggest relevant news articles to your users based on their past reading behavior.

Not ideal if you need a recommendation system that incorporates complex, handcrafted features beyond news content and user behavior for highly nuanced suggestions.

news-recommendation content-personalization media-platforms user-engagement digital-publishing
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 8 / 25
Community 17 / 25

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Stars

33

Forks

10

Language

Python

License

Last pushed

Mar 06, 2021

Commits (30d)

0

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