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The project report presents the HNVec-Driven MultiDL Framework for classifying Hindi news articles, aimed at enhancing content-based classification using various text embedding strategies. It evaluates the effectiveness of HNVec, a novel context-sensitive vectorizer, in combination with a hybrid learning model (HLM-CLS) against traditional methods like TF-IDF and FastText, achieving superior classification accuracy. The study highlights the importance of linguistically sensitive embeddings for Indian langua

Author

Akhil Rajput

Language

EN