{"id":246235,"date":"2021-12-24T04:44:21","date_gmt":"2021-12-24T04:44:21","guid":{"rendered":"https:\/\/imarticus.org\/?p=246235"},"modified":"2026-05-15T14:30:04","modified_gmt":"2026-05-15T09:00:04","slug":"heres-how-to-create-your-own-plagiarism-checker-with-the-help-of-python-and-machine-learning","status":"publish","type":"post","link":"https:\/\/imarticus.org\/blog\/heres-how-to-create-your-own-plagiarism-checker-with-the-help-of-python-and-machine-learning\/","title":{"rendered":"Here’s how to create your own plagiarism checker with the help of python and machine learning"},"content":{"rendered":"

Although plagiarism is not a legal concept, the general idea behind it is rather simple. It is about unethically taking credit for someone else’s work. However, plagiarism is considered dishonest and might lead to a penalty.\u00a0<\/span><\/p>\n

It is possible for coders to build their plagiarism checker in Python with the help of Machine Learning. Thus, it is advisable to undertake a <\/span>python course<\/b><\/a> to get a comprehensive idea about this programming language.\u00a0<\/span><\/p>\n

Here, you will get an idea of creating your own plagiarism checker. Once finished, individuals can check students\u2019 assessments to compare them with each other.\u00a0\u00a0<\/span><\/p>\n

\"Python
Python Is Perfect for AI and Machine Learning<\/figcaption><\/figure>\n

Pre-requisites<\/b><\/p>\n

To develop this plagiarism checker, individuals will need knowledge in python and machine learning techniques like cosine similarity and word2vec. <\/span><\/p>\n

Apart from these, developers must have sci-kit-learn installed on their devices. Hence, if anyone is not comfortable with these concepts, then they can opt for an <\/span>artificial intelligence and machine learning course<\/b><\/a>.\u00a0<\/span><\/p>\n

Installation\u00a0\u00a0\u00a0\u00a0<\/b><\/p>\n

How to Analyse Text\u00a0<\/b><\/p>\n

It is not unknown that computers only understand binary codes. So, before computation on textual data, converting text to numbers is mandatory.\u00a0<\/span><\/p>\n

Embedding Words\u00a0\u00a0<\/b><\/p>\n

Word embedding is the process of converting texts into an array of numerical. Here, the in-built feature of sci-kit-learn will come into play. The conversion of textual data into an array of numbers follows algorithms, representing words as a position in space.\u00a0<\/span><\/p>\n

How to recognize the similarities between the two documents?\u00a0<\/b><\/p>\n

Here, the basic concept of dot product can be used to check the similarity between two texts by computing the cosine similarity between two vectors.\u00a0<\/span><\/p>\n

Now, individuals need to use two sample text files to check the model. Make sure to keep these files in the same directory with the extension of .txt.<\/span><\/p>\n

Here is a look at the project directory \u2013\u00a0<\/span><\/p>\n

Now, here is a look at how to build the plagiarism checker\u00a0<\/b><\/p>\n