bobbyinfj/nlp-recommender
An NLP-based recommender system for the MIND-small dataset.
This project creates a system that predicts which news articles a user will click on, based on their past reading history and the titles/abstracts of articles. It takes in user interaction data and news content, and outputs a prediction (yes/no) for new articles. This is useful for anyone working in content personalization or digital publishing who wants to understand user engagement with news.
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Use this if you need a model to predict user engagement with news content, leveraging both past interactions and the textual content of articles.
Not ideal if your primary goal is to generate diverse or novel recommendations, as this model focuses on click prediction and doesn't explicitly optimize for those metrics.
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Last pushed
Feb 05, 2021
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