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.
Highlights
Introduction e number ofInternet users is growing rapidly, along with the fast development of the network applications and infrastructure
community question answering (CQA) sites provide a network platform for users to ask and answer questions and achieve information transfer and knowledge sharing among Internet users
We propose a new expert finding system containing expert ranking and expert recommendation for CQA sites
Summary
Internet users is growing rapidly, along with the fast development of the network applications and infrastructure. It follows that community question answering (CQA) sites spring up [3, 4]. CQA sites are online knowledge communities, specializing in knowledge sharing and seeking, such as Stack Overflow [5, 6] and Yahoo Answers [7]. CQA sites provide a network platform for users to ask and answer questions and achieve information transfer and knowledge sharing among Internet users. Due to various topics and abundance content in CQA sites, network users prefer CQA sites to conventional web pages when seeking topic-specific information or solving problems [8]. With the increasing number of community users, online communities amass an enormous amount of knowledge, which contains many useless answers inevitably in the community
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