Research and Develop A Machine Learning-Based Tool for Text Summarization

Abstract

People use social networks all around the world, with a plenty number of users, it still increases rapidly everyday. So the contents from these networks are very vast and needs to be thoroughly analyzed and exploited. The amount of text can be used for many different business purposes if we exploit and transform them in the orientation of a positive vision. To understand the large documents, we need to read all the texts, but it takes a lot of time to get all necessary information. So, how can we understand and get the key point of the documents without read full of it? Text summarization came to reduce the time, and make sure that we can get all the main information of a document. This project is about text summarization on social network data (Twitter and Facebook). With NLP models, we can analyze and summary these texts to get all the main points of users posts. From these main points, we can research and apply the results to many applications. These applications maybe online services, marketing plan, advertising, recommendation system for users over social networks. After experiments, we built a prototype (web app) for demonstration, which can present the practicality of the result of this project, details in these next sections.