Presented at the 2019 Wolfram Technology Conference.
Wolfram Language, Computational Linguistics, Machine Learning, Mathematica, Natural Language Processing, Fiction, Classification
Artificial Intelligence and Robotics | Computer Sciences | Physical Sciences and Mathematics
The objective of this project was to create a program that can determine whether an unknown text is a work of fiction or non-fiction using machine learning. Various datasets of speeches, ebooks, poems, scientific papers, and texts from Project Gutenberg and the Wolfram Example Data were utilized to train and test a Markov Chain machine learning model. A microsite was deployed with the final product that returns a probability of fictionality based on input from the user with 95% accuracy.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Classifying Fiction and Non-Fiction Works Using Machine Learning.
Retrieved from: https://digitalcommons.imsa.edu/student_pr/46