This is a Python application that uses Flask, pandas, matplotlib, sklearn, and nltk to detect plagiarism in text files. The application allows users to upload multiple text files and generates a report indicating the similarity between each pair of files.
The application is hosted at https://plagiarism-detector-dst6.onrender.com/
- Upload multiple text files for comparison
- Generate a similarity report in Excel format
- Visualize similarity between files with a heatmap /update/
- Use text box for pasting compared texts
- Show a tag clouds with the most common words in the text
- Display a scatter plot with 10 most common words
The application is containerized using Docker and hosted on Render. You can access it directly through the browser.
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On the home page, click "Choose Files" to select the text files you want to compare.
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Click "Upload" to upload the files and start the comparison.
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Once the comparison is complete, a heatmap displaying the similarity between each pair of files across the other tabs will be shown.
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Click "Download Report" to download an Excel file containing the similarity report.
- Add the ability to choose between different language models (MLE and WBI) for comparison and visualize perplexity.
- Add charts showing the dependency of the similarity measure on the length of the text.
- Compare computation time for different language models.
- Add charts showing the ratio of the number of words in the text to the entire text for each word and all texts on one chart (histogram) with the ability to choose the text for comparison (dropdown or radio buttons).