The Java Graphical Authorship Attribution Program
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Updated
Jul 6, 2024 - Java
The Java Graphical Authorship Attribution Program
✍️ An intelligent system that takes a document and classifies different writing styles within the document using stylometric techniques.
Collected solutions from Google Code Jam programming competition (2008-2020).
A package for generating CRediT (Contributor Role Taxonomy) statements
An authorship attribution system based on a machine learning model using syntactic linguistic information as a feature set.
Finding Gender/Age of Authors based on written text
Authorship Attribution of Tweets using Convolutional Neural Networks Over character n-grams
Implementation of Disjoint Author-Document Topic Model
Authorship Attribution in Social Media & Chat Biometrics & Behavioral Biometrics
Paper list for the paper "Authorship Attribution in the Era of Large Language Models: Problems, Methodologies, and Challenges"
Authorship Attribution with Machine Learning
A repository containing the source code, datasets, and ranked features for the Nested Bigrams method proposed in a paper published in ICDMW. This method is designed for authorship attribution in source code to address cybersecurity issues.
The Python Graphical Authorship Attribution Program — An experimental Python port of the Duquesne University Evaluating Variations in Language Lab's JGAAP.
Usage of stylometry and machine learning in computer forensics - real tools used in 2019 by the polish police. Everything in/for polish language.
Training ML/NN models to predict author, author's sex, and author's literary period given small snippet of text using NLTK, Gensim, Doc2Vec, Polygot, and Stanford NER
An Authorship Attribution Dataset for Detecting Human-Trafficking Operations on Escort Advertisements. (EMNLP 2023)
Stylometric analysis of poetic texts based on their versification
Comparison of classification power (literary authorship attribution case) of word-based, lemma-based, POS-based and mBERT-based document embeddings, as well as their combinations.
Курсовая работа по обработке данных
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