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A Research Paper Recommender based on a hybrid model that fetches this similarity from user preferences and a content based filtering approach

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Research-Nerd

A research paper recommender system built with ML algorithms and designed by pleasant UI/UX . This project contains a wide variety of tech stack namely React, Next JS, Tailwind CSS, Firebase, Flask, Python, Figma and a number of ML libraries to build an efficient model that recommends Top 10 papers. These recommendations are based on a hybrid model that fetches this similarity from user prefernces and a content based filtering approach.It has the following functionalities :

  1. Login/Register page
  2. Research engine
  3. Profile page
  4. Project upload page (in building stage)
  5. User Topic segment

We will soon be launching it with new updates

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A Research Paper Recommender based on a hybrid model that fetches this similarity from user preferences and a content based filtering approach

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  • TypeScript 61.6%
  • Jupyter Notebook 33.7%
  • Python 2.6%
  • JavaScript 2.1%