Text Summarization using TF-IDF and Textrank algorithm
Sarika Zaware, Deep Patadiya, Abhishek Gaikwad Gaikwad, Sanket Gulhane, Akash Thakare
Abstract
In this digital era, a tremendous amount of information gets generated every day. The generated information is used for multiple purposes such as scientific/medical research, news generation, blogs, etc. Reading and gathering the important information and summarizing it manually can become a tedious task which is also prone to manual errors. Therefore, more time is required to read that information, and also unwanted information gets mixed up with important information. It is difficult for a person to manually summarize a large document. Also, there is an issue with finding necessary documents and absorbing relevant information from them. In this proposed system, we are implementing a combination of TFIDF and Textrank algorithm with some NLP methods which will efficiently summarize the given data and will perform better than the other systems.