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.
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A Novel Expert Finding System for Community Question Answering
Semantic Scholar · Computer Science · 2020
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.
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