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Title: A research on the text reliability based on evidentiality
Authors: Su, QI
Chen, HKY
Huang, C 
Issue Date: 2011
Source: International journal of computer processing of languages, 2011, v. 23, no. 2, p. 201-214
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.
Keywords: Evidentiality
Collaborative question answering
Publisher: World Scientific
Journal: International journal of computer processing of languages 
ISSN: 1793-8406 (print)
2010-0205 (online)
DOI: 10.1142/S1793840611002292
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