Ranking user-created contents by search user's inclination in online communities

Searching posts effectively has become an important issue in large-scale online communities. Especially, if search users have different inclinations when they search posts, they have different kinds of posts in their minds. To address this problem, in this paper, we propose a scheme of ranking posts based on search users' inclination. User ranking score is employed to capture posts that are relevant to a specific user inclination. Specifically, we present a scheme to rank posts in terms of user expertise and popularity. Experimental results show that different user inclinations can produce quite different search results and the proposed scheme achieves about 70% accuracy.