Brainstorm optimization for multi-document summarization

Abstract

Document summarization is one of the solutions to mine the appropriate information from a huge number of documents. In this study, brainstorm optimization (BSO) based multi-document summarizer (MDSBSO) is proposed to solve the problem of multi-document summarization. The proposed MDSBSO is compared with two other multi-document summarization algorithms including particle swarm optimization (PSO) and bacterial foraging optimization (BFO). To evaluate the performance of proposed multi-document summarizer, two well-known benchmark document understanding conference (DUC) datasets are used. Performances of the compared algorithms are evaluated using ROUGE evaluation metrics. The experimental analysis clearly exposes that the proposed MDSBSO summarization algorithm produces significant enhancement when compared with the other summarization algorithms.