AbstractsComputer Science

Question Routing systems aim at routing questions to users that are more suited to answer them. Different techniques are used to match candidate users to questions, by considering properties of both. Existing techniques however do not consider the expertise of the candidate. This work proposes an approach to Question Routing in which the user expertise is considered for question routing purposes. The proposed approach is a three stage process which allows for different configurations of existing matching techniques and user expertise. An experiment is set up in order to compare different Question Routing configurations. In total thirteen different configurations are evaluated, all based on three different content-based baseline methods. Stack Overflow is used as the source for questions, answers and users for the evaluation of the performance of different Question Routing configurations. A dataset containing 6 months worth of questions is used for the evaluation. The results show that incorporating expertise into Question Routing algorithms can provide significant performance increase.