A social recommender mechanism for improving knowledge sharing in online forums

Nowadays, online forums have become a useful tool for knowledge management in Web-based technology. This study proposes a social recommender system which generates discussion thread and expert recommendations based on semantic similarity, profession and reliability, social intimacy and popularity, and social network-based Markov Chain (SNMC) models for knowledge sharing in online forum communities. The advantage of the proposed mechanism is its relatively comprehensive consideration of the aspects of knowledge sharing. Accordingly, results of our experiments show that with the support of the proposed recommendation mechanism, requesters in forums can easily find similar discussion threads to avoid spamming the same discussion. In addition, if the requesters cannot find qualified discussion threads, this mechanism provides a relatively efficient and active way to find the appropriate experts.

► We build a social recommender system for knowledge sharing in online forums.
► The system finds relevant threads and experts efficiently to avoid spamming.
► The system integrates similarity, expertise, relation, and SNMC analysis modules.
► The system has better precision and recall rates than other benchmark methods.