Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/34621
Title: Sequential summarization : a full view of Twitter trending topics
Authors: Gao, D
Li, W 
Cai, X
Zhang, R
Ouyang, Y
Issue Date: 2014
Publisher: IEEE
Source: IEEE transactions on audio, speech and language processing , 2014, v. 22, no. 2, p. 293-302 How to cite?
Journal: IEEE transactions on audio, speech and language processing
Abstract: As an information delivering platform, Twitter collects millions of tweets every day. However, some users, especially new users, often find it difficult to understand trending topics in Twitter when confronting the overwhelming and unorganized tweets. Existing work has attempted to provide a short snippet to explain a topic, but this only provides limited benefits and cannot satisfy the users' expectations. In this paper, we propose a new summarization task, namely sequential summarization, which aims to provide a serial of chronologically ordered short sub-summaries for a trending topic in order to provide a complete story about the development of the topic while retaining the order of information presentation. Different from the traditional summarization task, the numbers of sub-summaries for different topics are not fixed. Two approaches, i.e., stream-based and semantic-based approaches, are developed to detect the important subtopics within a trending topic. Then a short sub-summary is generated for each subtopic. In addition, we propose three new measures to evaluate the position-aware coverage, sequential novelty and sequence correlation of the system-generated summaries. The experimental results based on the proposed evaluation criteria have demonstrated the effectiveness of the proposed approaches.
URI: http://hdl.handle.net/10397/34621
ISSN: 2329-9290
DOI: 10.1109/TASL.2013.2282191
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

3
Citations as of Apr 30, 2016

WEB OF SCIENCETM
Citations

3
Last Week
1
Last month
Citations as of Feb 20, 2017

Page view(s)

18
Last Week
2
Last month
Checked on Feb 19, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.