A news article recommendation system written in python. Utilized term frequence - inverse document frequency to generate tags for invidual news articles. Then used the vector of tags to run a K-means clustering algorithm to cluster articles. User inputs some article they read and the program generates 5 article recommendations. final_project.py file has instructions on how to run.
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