A Novel Expert Finding System for Community Question Answering

Joint Authors

Cheng, Peng
Xiong, Fei
Cheng, Jia
Chen, Nan
Zhao, Nan

Source

Complexity

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

Philosophy

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