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: 04 Mar 2020 *

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