Acquiring networks of trust relations among users in social media sites such as item-review sites is important for analyzing users' behaviour and efficiently finding reliable information on the Web. For an item-review site, we address the problem of predicting trust-links among users. Recently, non-negative matrix factorization (NMF) methods have been shown to be useful for trust-link predition in such an site, where both the link and activity information is employed. Here, a user activity in an item-review site means posting a review and giving a rating for an item. Aiming to improve NMF methods for trust-link prediction, in this paper, we propose such an NMF method that incorporates information of people's evaluations for users' activities as well as information of trust-links and users' activities. Also, we apply it to an analysis of users' behaviour. Using real data of an item-review site, we experimentally demonstrate the effectiveness of the proposed method.