大多数移动社会性软件搜索方法缺乏对用户物理位置和社会性的兼顾研究。针对这种情况,提出了一种基于兴趣和位置的移动社会性软件搜索方法,通过设置不同功能类型的超级节点将覆盖层网络分层,从而兼顾了节点的社会性和物理位置。为了提高查询效率,引入了查询度的概念,节点的查询和位置更新均受其查询度的影响。实验结果表明,相比传统算法该方法在平均响应时间和查询效率上有显著提高。
Most mobile social software's search methods lack research of both users'physical location and sociality.To this problem this paper proposes a mobile social software search scheme based on interest and location.The overlay is layered through setting different kinds of super-nodes.Thus the nodes'sociality and location are considered.In order to improve the query efficiency,this paper introduces the concept of query degree.In the process of searching and updating,the query degree has greater influence.Compared with traditional algorithm,experimental results show that the approach is effective in average response time and query efficiency.