Extractive Text Summarization using Meta-heuristic Approach

Abstract

This paper describes a system for Indian Language Extractive Summarization which has been developed under the shared task ILSUM of FIRE 2022[1][2] Conference by SUMIL22 team. This system works by picking up sentences directly from the text using a ranking function to form the corresponding summary. In our approach, for each sentence, we first calculated various text features such as sentence position, sentence length, sentence similarity, frequent words, and sentence numbers. Then, these text features along with their optimized weights are used for ranking the sentences, and then the summary is generated by selecting top-ranked sentences. For optimizing the weights of the text features, we have used a population based meta-heuristic approach, Genetic Algorithm (GA). We submitted three runs and got an F-score of 0.3843 for ROUGE-1, 0.2584 for ROUGE-2, 0.1997 for ROUGE-3 and 0.2190 for ROUGE-4 in the best run. © 2022 Copyright for this paper by its authors.