A Hybrid Model for Summarizing Text Documents Using Text Rank Algorithm and Term Frequency

Abstract

   The amount of data available online in today's world is largely unstructured and very difficult to summarize the entire content and change it into the appropriate form of information. The volume of unstructured data is demanding the need for automatic systems which are capable of compacting information from different records into a simple, concise description. This paper aims to generate text summarization by combining TF-IDF and Text Rank algorithm to achieve better results than the existing methods. The summary is evaluated using the Rouge metric.