Multi-document text summarization using sentence extraction

Abstract

This paper presents a method for generating multi-document text summary building on single document text summaries and by combining those single document text summaries using cosine similarity. For the generation of single document text summaries features like document feature, sentence position feature, normalized sentence length feature, numerical data feature, and proper noun feature are used. Single document text summaries are combined after calculating cosine similarity between the different single document text summaries generated and from each combination, sentences with high total sentence weight are extracted to generate multi-document text summary. The average F-measure of 0.30493 on DUC 2002 dataset has been observed, which is comparable to two of five top performing multi-document text summarization systems reported on the DUC 2002 dataset.