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.
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Updated
Jan 16, 2026 - Jupyter Notebook
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.
GSMA telecom documentation dataset creation pipeline with hard negative generation for embedding training. Features concurrent LLM validation, semantic similarity ranking, and DVC-based reproducible data processing.
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