You might be wondering on how plagiarism detection on textual data is done, well it aint that complicated as you may think.
We all all know that computer are good at numbers, so in order to compute the simlilarity between on two text documents, the textual raw data is transformed into vectors => arrays of numbers and then from that we are going to use a basic knowledge vector to compute the the similarity between them.
This repo consist of a basic example on how to do that.
To get started with the code on this repo, you need to either clone or download this repo into your machine just as shown below;
git clone https://github.com/aditpatel01/AI-Mini-ProjectBefore you begin playing with the source code you might need to install deps just as shown below;
pip3 install -r requirements.txtTo run this code you need to have your textual document in your project directory with extension .txt and then when you run the script, it will automatically loads all the document with that extension and then compute the similarity between them just as shown below;
$-> cd Plagiarism-checker-Python
$ Plagiarism-checker-Python-> python3 app.py
('john.txt', 'juma.txt', 0.5465972177348937)
('fatma.txt', 'john.txt', 0.14806887549598566)
('fatma.txt', 'juma.txt', 0.18643448370323362)