NLP Based TextRank Algorithm for Automatic Text Summarization: An Unsupervised Approach

Authors

  • K.Chandra Kumar, Dr.Sudhakar Nagalla, B.P.N.Madhu Kumar

Abstract

A time-consuming process in which people seek primarily relevant information on the Internet, is the
method used for obtaining and processing knowledge from various sources. The primary objective of the
program is to eliminate information from the website and to provide information from information collected
from other websites that enables users to choose the website that they need. The analysis of data, removal of
outliers and information on the database initiates a sequence of steps, highlights the significance of relevant data
collected from the site and offers a summary of collected information. Natural language analysis shall be
employed to extract the useful information from the acquired data. In this paper, Natural language processing
(NLP) based TextRank algorithm for automatic text summarization which is an unsupervised approach has been
proposed and analysed properly. This proposed approach has been compared with Artificial bee colony
algorithm and Cuckoo search algorithm, thereby the proposed methodology shows better outcomes when
compared to conventional methods. This proposed approach will minimize the browsing time required and will
allow users to sum up the links, documents or keywords on a particular website or document.

Published

2020-05-30

Issue

Section

Articles