Routing Questions to the Right Users in Online Communities

Online forums contain huge amounts of valuable user-generated content. In current forum systems, users have to passively wait for other users to visit the forum systems and read/answer their questions. The user experience I or question answering suffers from this arrangement. In this paper, we address the problem of "pushing" the right questions to the right persons, the objective being to obtain quick, high-quality answers, thus improving user satisfaction. We propose a framework for the efficient and effective routing of a given question to the top-k potential experts (users) in a forum, by utilizing both the content and structures of the forum system. First, we compute the expertise of users according to the content of the forum system-this is to estimate the probability of a user being an expert for a given question based on the previous question answering of the user. Specifically, we design three models for this task, including a profile-based model, a thread-based model, and a cluster-based model. Second, we re-rank the user expertise measured in probability by utilizing the structural relations among users in a forum system. The results of the two steps can be integrated naturally in a probabilistic model that computes a final ranking score for each user. Experimental results show that the proposals are very promising.Computer Science, Software EngineeringComputer Science, Theory & MethodsEngineering, Electrical & ElectronicEICPCI-S(ISTP)2