Document Type

Conference Paper/Presentation

Conference

Presented at the 2019 Wolfram Technology Conference.

Publication Date

10-29-2019

Keywords

Wolfram Language, Computational Linguistics, Machine Learning, Mathematica, Natural Language Processing, Fiction, Classification

Disciplines

Artificial Intelligence and Robotics | Computer Sciences | Physical Sciences and Mathematics

Abstract

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

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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