A scalable two-stage news recommender that retrieves relevant candidates and reranks them using hybrid lexical and semantic features to optimize top-K recommendation quality.
nlp xgboost logistic-regression hit ndcg priors lexical-semantics mlp-classifier mrr distilbert microsoft-newsqa-dataset candidate-generation content-similarity ranking-models hard-negatives news-recommendation-system mind-dataset ndcg-ranking
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Updated
Jan 16, 2026 - Jupyter Notebook