Extractive Text Summarization Using Modified Weighing and Sentence Symmetric Feature Methods

Text Summarization is a process that converts the original text into summarized form without changing the meaning of its contents. It finds its usefulness in many areas when the time to go through a large content is limited. This paper presents a comparative evaluation of statistical methods in extractive text summarization. Top score method is taken to be the bench mark for evaluation. Modified weighing method and modified sentence symmetric feature method are implemented with additional characteristic features to achieve a better performance than the benchmark method. Thematic weight and emphasize weights are added to conventional weighing method and the process of weight updation in sentence symmetric method is also modified in this paper. After evaluating these three methods using the standard measures, modified weighing method is identified as the best method with 80% efficiency.