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Demonstration notebooks for processes to reduce volume of news articles relative to some topic. Runnable in Binder.

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Demo for News Article Collection and Volume Reduction Pipeline

Binder

Brief notebooks that run through the following processes using a dataset of NYT Front Page articles

  1. Find efficient keywords with word embeddings (gensim)
  2. Remove duplicitous articles with cosine similarity on TFIDF vectors (scikit-learn)
  3. Remove duplicitous articles with entity extraction and jaccard similarity (spacy)
  4. Classify relevant articles (scikit-learn)

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Demonstration notebooks for processes to reduce volume of news articles relative to some topic. Runnable in Binder.

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