Automatic document summarization
Ong, Yu En
Date of Issue2018
School of Electrical and Electronic Engineering
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.
Final Year Project (FYP)
Nanyang Technological University