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code_.ipynb
requirements.txt

# News Article Ranking Using FastText, LSI, BERT and GloVe Algorithms ## Overview This project is done by Ena Medic and Katarina Zelenika from Group 35. The main objective is to implement and compare different algorithms to generate a ranked list of news articles based on their relevance to a given search query. ## Team Members - **Ena Medic**: Responsible for implementing LSI (Latent Semantic Indexing), FastText, and grading of ranks. - **Katarina Zelenika**: In charge of implementing BERT, GloVe, and creating necessary visualizations and descriptions for the project. ## Data Source Our primary data source will be NewsAPI, which provides a simple HTTP REST API for accessing the most recent news articles. ## Project Goals - Implement different NLP algorithms: LSI, BERT, FastText, and GloVe. - Compare the effectiveness of these algorithms in ranking news articles. - Evaluate the ranked lists using metric MRR

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