A language independent approach to multilingual text summarization

Abstract

This paper describes an efficient algorithm for language independent generic extractive summarization for single document. The algorithm is based on structural and statistical (rather than semantic) factors. Through evaluations performed on a single-document summarization for English, Hindi, Gujarati and Urdu documents, we show that the method performs equally well regardless of the language. The algorithm has been applied on DUC data for English documents and various newspaper articles for other languages with corresponding stop words list and modified stemmer. The results of summarization have been compared with DUC 2002 data using degree of representativeness. For other languages, the degree of representativeness we get is highly encouraging.