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A Novel Expert Finding System for Community Question Answering
Joint Authors
Cheng, Peng
Xiong, Fei
Cheng, Jia
Chen, Nan
Zhao, Nan
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-23
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
With the popularity of community question answering (CQA) sites, the research on identifying the expert users in online communities attracted increasing attention.
We present a novel expert ranking algorithm based on the quality of user posts and the authority of user in community, and the similarity between the knowledge tags of users and questions in CQA sites is adopted in our scheme.
Experimental results show that our scheme has better performance and accuracy under the same background with an amount of data samples.
American Psychological Association (APA)
Zhao, Nan& Cheng, Jia& Chen, Nan& Xiong, Fei& Cheng, Peng. 2020. A Novel Expert Finding System for Community Question Answering. Complexity،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1142403
Modern Language Association (MLA)
Zhao, Nan…[et al.]. A Novel Expert Finding System for Community Question Answering. Complexity No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1142403
American Medical Association (AMA)
Zhao, Nan& Cheng, Jia& Chen, Nan& Xiong, Fei& Cheng, Peng. A Novel Expert Finding System for Community Question Answering. Complexity. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1142403
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142403