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There are several online newspapers in urdu but for the users it is difficultto find the content they are looking for because these most of them containirrelevant data and most users did not get what they want to retrieve. Ourproposed framework will help to predict Urdu news in the interests of users andreduce the users searching time for news. For this purpose, NLP techniques areused for pre-processing, and then TF-IDF with cosine similarity is used forgaining the highest similarity and recommended news on user preferences.Moreover, the BERT language model is also used for similarity, and by using theBERT model similarity increases as compared to TF-IDF so the approach worksbetter with the BERT language model and recommends news to the user on theirinterest. The news is recommended when the similarity of the articles is above60 percent.

Urdu News Article Recommendation Model using Natural Language Processing Techniques