A Survey on Expert Recommendation in Community Question Answering
Xianzhi Wang, Chaoran Huang, Lina Yao, Boualem Benatallah, Manqing, Dong

TL;DR
This survey reviews expert recommendation techniques in community question answering, highlighting their advantages, shortcomings, and future research directions to improve matching between questions and experts.
Contribution
It provides a comprehensive overview and comparison of existing expert recommendation methods in CQA, identifying open issues and future research directions.
Findings
Various expert recommendation methods have been developed with distinct advantages.
Current methods face challenges like accuracy and scalability.
Open issues include improving relevance and timeliness of recommendations.
Abstract
Community question answering (CQA) represents the type of Web applications where people can exchange knowledge via asking and answering questions. One significant challenge of most real-world CQA systems is the lack of effective matching between questions and the potential good answerers, which adversely affects the efficient knowledge acquisition and circulation. On the one hand, a requester might experience many low-quality answers without receiving a quality response in a brief time, on the other hand, an answerer might face numerous new questions without being able to identify their questions of interest quickly. Under this situation, expert recommendation emerges as a promising technique to address the above issues. Instead of passively waiting for users to browse and find their questions of interest, an expert recommendation method raises the attention of users to the appropriate…
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Taxonomy
TopicsExpert finding and Q&A systems · Topic Modeling · Speech and dialogue systems
