Multi-document summarisation using feature distribution analysis
by Jae-Young Chang
International Journal of Computational Vision and Robotics (IJCVR), Vol. 10, No. 2, 2020

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.

Online publication date: Mon, 09-Mar-2020

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Vision and Robotics (IJCVR):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com