Automatic document summarization

• Main Author: Ong, Yu En
• Other Authors: Mao Kezhi
• Format: Final Year Project
• Language: English
• Published: 2018
• Subjects: DRNTU::Engineering
• Online Access: http://hdl.handle.net/10356/75182
• Institution: Nanyang Technological University

As the information on the internet continues to expand exponentially, machine learning, is becoming more and more important. Therefore, text summarization, a branch of Natural Language Processing (NLP), has increasingly become a topic of interest to many researcher as it is becoming a method to retrieve huge amount of data from the web. This project aims to explore the techniques used to conjure an Automatic Document Summarizer. It consists of different representation learning model and clustering techniques algorithm and finally a summarized version of the original document using a certain amount of key sentences. There are a total of 6 combinations involved when determining the accuracy of the technique. This report will also discuss the theory behind the method used and how does it affect the overall results of the summarizer.