REC: A Novel Model to Rank Experts in Communities

Abstract

It is an important issue to get support from experts in our daily life. Expert finding is challenging. In previous commercial and academic systems, the users may not get what they expect. In this contribution, we address the problem of finding experts in communities. A novel model REC is presented to solve the expert finding problem in dynamic environment. The model ranks experts by textural and social information. Starting with the most familiar communities, the expert seeker may find appropriate experts, by considering both their local rankings in each community and the difficulty to get their help. Experiments are done on real data sets, including DBLP data set and W3C corpora. Compared with other existing methods, REC achieves promising results. It demonstrates the model's competencies in various search applications.