This repository contains the research paper An Evaluation of Modern Text Summarization Methods, which was submitted as a final project for the course COMP 4750 - Natural Language Processing during my senior year. The paper explores and compares various state-of-the-art text summarization techniques, and provides insights into their performance and effectiveness.
The research paper delves into the following topics:
- Introduction to text summarization and its importance in the era of information overload.
- Overview of different text summarization approaches, including extractive and abstractive methods.
- Analysis of current state-of-the-art text summarization models, such as BERT, GPT, and T5.
- A detailed comparison of these models in terms of accuracy, coherence, and efficiency.
- Discussion on the challenges and future prospects of text summarization research.
To read the research paper, simply download or view the PDF file available in the repository.
This research paper is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. You are free to share (copy and redistribute) the material, as long as you give appropriate credit, do not use the material for commercial purposes, and do not distribute modified versions of the paper.
If you find this research paper useful in your own work, please consider citing it as follows:
Joshua Peddle. (2022). An Evaluation of Modern Text Summarization Methods. Senior Year Final Project, COMP 4750 - Natural Language Processing. Retrieved from https://github.com/JoshuaPeddle/text-summarization-evaluation
For any further inquiries, please feel free to reach out to me via email at [email protected].
Happy reading!