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Lingle

Xinyi Ji, Allegra Chen, Jingfei Tan

Website of Lingle

Inspiration

  • Being a student we have to read a lot of research paper to learn something new. Being a citizen we read news of different countries, different organizations with the developent of globalization. But with so many articles to read we only have limit time. Therefore, trying to find what is really useful in a short time is really useful for people nowadays.

Introduction to this project

  • Trying to read news or a research paper but the article is too long to read? Paste the article on the website posted above and Lingle will help you highlight the significant sentences in the article, and then it will be much easier for you to read!

Basic Functions

  • After pasting the whole article on the dialog box and click on the analyse button, Lingle will show you the same article with significant sentences highligted with different colours (red is for positive attitude, blue is for negative and the yellow is somewhat between these two). Then you can now read the text much easier by just looking at the sentences highlighted and knowing what kind of attitude these sentences represented.

Great Features

  • With different colours to highlight the sentences, users can get the general attitude of the whole article by just skim the colours of the article.

How we built it

  • The project is built in python and we also use the Natural Language Machine Learning APIs from Google to analyze the context of the article ( Thanks Google).

Challenges we ran into

  • We spent some time trying to show the context on the website with python connecting with html, css, Django framework which will highlight the sentences.

What we learned

  • We learnt how to use the API and how to create a website.

What's next

  • Continue to work on it to improve the interface and add more features.

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