A Novel Expert Finding System for Community Question Answering

Author:

Zhao Nan1ORCID,Cheng Jia1,Chen Nan1,Xiong Fei2,Cheng Peng3

Affiliation:

1. State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an 710071, China

2. Key Laboratory of Communication & Information Systems, Beijing Jiaotong University, Beijing 100044, China

3. Space Star Aerospace Technology Applications Limited Corporation, Xi’an 710077, China

Abstract

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.

Funder

Key Industry Projects in Shaanxi Province

Publisher

Hindawi Limited

Subject

Multidisciplinary,General Computer Science

Reference47 articles.

1. Learning to recognize reliable users and content in social media with coupled mutual reinforcement;J. Bian

2. Identifying authoritative actors in question-answering forums: The case of Yahoo! answers;M. Bouguessa

3. A method to automatically construct a user knowledge model in a forum environment;A. Kardan

4. Deep learning for community detection: progress, challenges and opportunities;F. Liu

5. What are developers talking about? An analysis of topics and trends in Stack Overflow

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