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learn.ai

making learning smarter

The problem learn.ai solves

The pandemic forced people to shift from physical classes to online ones and turn to digital resources. No doubt the information is abundant, but how can one process all of the available information?

That is where our project steps in, using the latest NLP techniques, we have made the process of learning new concepts a much easier task for students. Our project has 3 core features:

  1. Text Summarization:
    We use text summarization to give the user a more concise idea about the topic. The text summarization allows for different biases i.e. general sciences, financial, historical and normal summarization. A list of domain specific terminologies are created using web scraping to apply these biases

  2. Mind Maps:
    The second aspect of the project is to give a visual representation of the text so that visual learners can benefit from it. It uses entity extraction via pattern matching and then finds the relation between them.

  3. Question Generation:
    The project also has a testing system that allows the user to test the knowledge that they have assimilated. We use pattern matching algorithms to formulate the questions based on the input texts. This helps the user to check the facts and go through those topics again for better preparation.

Online education has become the new norm and we believe every single human deserves quality education as well as support. Our project aims to assist every student to learn using the best technologies and via innovative techniques such as mind maps, automatic question generation and cutting down on large texts to contain only the core details. We have a vision to make sure that in this vast world of knowledge, no child is left without support. Our goal is to ensure everyone has access to this platform and your support would be greatly appreciated to help us achieve this dream of a smarter world.

Challenges we ran into

This project was initially done in Flask. We decided to shift it to Django so that our project could be made more scalable and have the potential to add a mobile application, enabling it to be used everyone and anywhere! We had plans to make an app for the project in addition to the website, but weren't able to do it because we faced a lot of issues trying to host the server.
Another issue that we faced was related to compatibility. Some of the code segments weren't working on macOS and we realised that during the process of saving files, there were minor differences between macOS and other operating systems. Fortunately, we were able to solve the issue and make sure our website worked seamlessly across all platforms.

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