Title: Multi-document summarisation using feature distribution analysis
Authors: Jae-Young Chang
Addresses: Department of Computer Engineering, Hansung University, Seoul, South Korea
Abstract: Recently, opinion documents have been growing rapidly in an environment where anyone can express an opinion on the internet or SNS. This situation requires an automatic summarisation technique in order to understand the contents of large-scale opinion documents. However, it is not easy to summarise the opinion documents with previous text summarisation technologies since the opinion documents include subject expressions, as well as features of targets objects. In this paper, a method to identify and extract the representative documents with a large amount of opinion documents is proposed. In addition, experiments show that the proposed method successfully extracts representative opinion documents.
Keywords: multi-document summarisation; opinion document; feature distribution; text mining; social network service; SNS; movie reviews; topic.
DOI: 10.1504/IJCVR.2020.105681
International Journal of Computational Vision and Robotics, 2020 Vol.10 No.2, pp.111 - 121
Received: 06 Feb 2019
Accepted: 10 Apr 2019
Published online: 09 Mar 2020 *