Importing Libraries
With just one line of code, Python libraries make it exceedingly simple for us to manage the data and finish both straightforward and challenging tasks.
- Matplotlib: It is used to represent data visually and helps to create visual representations of huge amount of data that can be easy to use and understand.
- OS : It is an in-built module in python that helps interact with operating system. It provide a portable method of utilizing operating system-specific functionality. There are number of functions to deal with the file system in the *os* and *os.path* modules.
- Scikit-Learn: It is an open-source python toolkit called scikit-learn that uses a uniform interface to implement a variety of machine learning, pre-processing, cross-validation, and visualization methods.
Let’s start importing libraries
Python3
#importing libraries for model building import os import matplotlib.pyplot as plt from sklearn.feature_extraction.text import TfidfVectorizer from sklearn.metrics.pairwise import cosine_similarity from wordcloud import WordCloud |
- Tf-idfvectorizer – Converts documents into matrix of TF-IDF features
- Cosine similarity- It is the cosine of the angle between two vectors.
- Sklearn.feature_extraction.text – Used to extract the features from data made up of formats like text and image that can be processed by ML algorithms.
- Skearn.metrics.pairwise – It offers tools for assessing the similarity or pairwise distances between collection of samples.
Plagiarism Detection using Python
In this article, we are going to learn how to check plagiarism using Python.
Plagiarism: Plagiarism basically refers to cheating. It means stealing someone’s else work, ideas, or information from the resources without providing the necessary credits to the author. For example, copying text from different resources from word to word without mentioning any quotation marks.
Table of Content
- What is Plagiarism detection?
- Importing Libraries
- Listing and Reading Files
- TF-IDF Vectorization
- Calculating Cosine Similarity
- Creating Document-vector Pairs
- Checking Plagiarism
- Word Cloud Visualization
- Conclusion
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