Please use this identifier to cite or link to this item:
Title: A research on the text reliability based on evidentiality
Authors: Su, QI
Chen, HKY
Huang, C 
Keywords: Evidentiality
Collaborative question answering
Issue Date: 2011
Publisher: World Scientific
Source: International journal of computer processing of languages, 2011, v. 23, no. 2, p. 201-214 How to cite?
Journal: International journal of computer processing of languages 
Abstract: In this paper, we focus on the reliability of information encoded in a Web 2.0 community platform. Specifically, we aim to explore how linguistically encoded clues can contribute to the task. Given that evidentiality is the linguistic representation for the reliability of a statement, we propose to use evidential, the lexicalized evidentiality, to model text representation under the framework of machine learning based text classification. Based on the model, we conducted experiments to identify the best answers in Collaborative Question Answering (CQA) services. The experimental results confirm that, incorporating evidential for predicting text reliability is effective, since it shows the writer's self-judgment for information reliability. Moreover, our method can largely reduce the dimensionality of the vector space, and therefore provide an improvement in efficiency.
ISSN: 1793-8406 (print)
2010-0205 (online)
DOI: 10.1142/S1793840611002292
Appears in Collections:Journal/Magazine Article

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

Page view(s)

Last Week
Last month
Citations as of Oct 14, 2018

Google ScholarTM



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