✍️ An intelligent system that takes a document and classifies different writing styles within the document using stylometric techniques.
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Updated
Aug 6, 2024 - Python
✍️ An intelligent system that takes a document and classifies different writing styles within the document using stylometric techniques.
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
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.
Usage of stylometry and machine learning in computer forensics - real tools used in 2019 by the polish police. Everything in/for polish language.
The Python Graphical Authorship Attribution Program — An experimental Python port of the Duquesne University Evaluating Variations in Language Lab's JGAAP.
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.
Authorship Attribution for Romanian
Ataurus is Attribution of Authorship Russian. The program to identify authors of russian texts.
A Python library that allows easy extraction of a variety of text units within texts...
📚📊 BayesianBookworm: A text analysis tool utilizing Bayesian inference to attribute authorship of literary works, initially focusing on the distinctive styles of Austen and Dickens.
Explainable Writing Style Detection with User Interface
A collection of python scripts / jupyter notebooks to construct various datasets across NLP and CV topics.
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