comparison analysis between two texts

API para detecção de plágio em código

A Java program to check Plagiarisms between multiple documents using the method of Shingling, MinHashing and Locality Sensitive Hashing.

This is a simple program that detects plagiarism by using the content of txt file as a searching keyword, and display the highest percentage of matching out of the first page of google search result. It uses google search API to do the search.

Simple client for Moss plagiarism analyzer

Deep Image Similarity with TensorFlow Keras.

This repository hosts a project that aims to tackle the issue of plagiarism in handwritten submissions. The system developed based on Multi-level detection using the combination of digital pattern analysis and text content comparison to detect potential instances of plagiarism.

Use concept of document distance to detect plagiarism in text

A simple plagiarism detection program

Plagiarism Detection Model Deployment Using Amazon SageMaker

PlagDetect é um projeto que tem como principal função a detecção de plágio em trabalhos submetidos por pesquisadores de uma determinada instituição.

A simple MinHash implementation based on the explanation in the Mining of Massive Datasets course by Stanford

Plagiarism plugin for Moodle LMS which allows for metered, on demand usage as opposed to "submit by default".

Plagiarism Detector with Amazon sagemaker - Udacity ML Nanodegree

A Plagiarism detector deployed using AWS Sagemaker for the purpose of determining how similar the text file is to a provided source text.

Build and deploy a plagiarism detector that classifies text files as plagiarised or not.

Udacity project to build a plagiarism detector that examines a text file and performs binary classification. Classification models used are Linear Learner, Random Forest Classfier and Neural Network, which are trained and deployed on AWS Sagemaker. The text file is labeled as either plagiarized or not, depending on how similar that text file is …

A website for checking and calculating the percentage of similarity between the graduation projects