Listing and Reading Files

Let’s now prepare the document data and read the context in the data.

Python3




# Get a list of student files
student_file = [file for file in os.listdir() if file.endswith('.txt')]
  
# Read the content of each student's file
student_docs = [open(file).read() for file in student_file]
  
# Print the list of student files and their content
for filename, document in zip(student_file, student_docs):
    print(f"File: {filename}")
    print("Content:")
    print(document)
    print("-" * 30# Separator between documents


output:

File: fatma.txt
Content:
Lorem Ipsum is simply dummy text of the printing and typesetting industry.
Lorem Ipsum has been the industry's
standard dummy text ever since the 1500s,
------------------------------
File: john.txt
Content:
t is a long established fact that a reader will be distracted by the readable content of
a page when looking at its layout.
The point of using Lorem Ipsum
------------------------------
File: juma.txt
Content:
t is a long established fact that a reader will
be distracted by the readable content of a
page when looking at its layout. The point of using Lorem Ipsum
------------------------------

Here, in this code, it collects a list of the student text files, reads their content and prints both the file names and their respective content, making it useful for inspecting and working with the content of the files.

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

Similar Reads

What is Plagiarism detection?

...

Importing Libraries

The crucial procedure of detecting plagiarism aims to identify situations in which someone has directly copied or closely resembled the work the work of others without giving due credit. In order to assess a text’s originality, it must be compared to a variety of previously published works. In order to uphold uniqueness in creative works, maintain academic integrity, and ensure the reliability of research and information, plagiarism must be found. In this article, we’ll look at how to use Python to construct an automated program to find instances of plagiarism so that we can quickly find and deal with them....

Listing and Reading Files

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....

TF-IDF Vectorization

...

Calculating Cosine Similarity

Let’s now prepare the document data and read the context in the data....

Creating Document-vector Pairs

...

Checking Plagiarism

TF-IDF (Term Frequency-Inverse Document Frequency) is a metric that quantifies the value of a term in a document in relation to a group of documents and is used in natural language processing. It is frequently employed in text mining, information retrieval, and text analysis....

Word Cloud Visualization

...

Conclusion

Cosine Similarity is a metric that assesses how similar two non-zero vectors are to one another in an n-dimensional space. It is frequently used in text analysis to compare the vector representations of two documents to ascertain how similar they are....

Contact Us