A Content-Aware Expert Recommendation Scheme in Social Network Services

Because a wide range of professionals utilize Social Network Service (SNS), the SNS users have recently required an expert recommendation service to enable users to perform both cooperation and technical communication with experts. A content-boosted collaborative filtering (CBCF) provides various prediction algorithms which support effective recommendations. However, the CBCF cannot calculates the similarity of items (or users) when the calculation condition is not clearly provided. To solve the problem, we propose a content-aware hybrid collaborative filtering scheme for expert recommendation in SNSs. Finally, we show from a performance analysis that our scheme outperforms the existing method in terms of recommendation accuracy.