中文摘要：

随着在线社交网络的快速发展,用户信息和用户规模呈现爆炸性增长,如何从网络上获取有针对性的信息已非易事,为此各种推荐系统已先后涌现.为各类不同用户以自然的推荐方式向其推荐信息并获得较高的用户采纳度是一件富挑战性的工作,也是本文的主要研究内容.如何在特定专业性拓扑网络中寻找到自然的推荐方式以得到较好的用户采纳度,是本文将要解决的问题.基于此,本文采用对潜在角色和关系预测研究,以E-CARGO模型为理论背景,针对专业性教学科研平台——学者网,通过对用户推荐内容信息,先形成与用户的信息交互,再根据信息交互程度,推荐相应的论文研究团队,推动关系结构的形成.本次调查实验结果体现了普遍用户愿意以3.9785分采纳团队推荐,用户平均满意度达79.57%,充分证明了这样的推荐方式使得用户更容易接受团队推荐信息,增强用户体验,为专业性学术论文网站学者网提供了指引.

英文摘要：

With the rapid development of SNS, user information and user scale showed explosive growth. Target information obtained from the Internet is very difficult, therefore, has appeared in a variety of recommendation systems. Using natural way to recommend in- formation for different user, and to obtain a higher degree of user adoption, it is challenging job. Simultaneously, it is the main contents of this paper. We want to solve the problem is how to obtain better user adoption,by finding a natural recommended way on specific topology of the network. Based on this, studies scholars network by adopting the potential role and relations forecast ~moreover~theoret- ical background is E-CARGO model. By recommending information to the user, first, the information exchange between users, then ac- cording to the degree of information exchange, recommend appropriate team and promoting relational. It proves that can make user more easily to accept groups, at the same time, enhance the user experience, provide guidance for scholars network.