摘要
如何通过情景感知,获得用户的行为特征,从而自动发现潜在的社会关系,是移动社交网络重要的研究内容之一.该文提出了情景感知的移动P2P社交网络系统架构、聚合模型及发现算法,将用户的位置信息、环境特征、运动轨迹等引入到聚合算法中,智能地聚合成潜在的P2P社交网络,根据用户需求自主发现匹配的社会关系,避免了社交活动的盲目性和随意性.最后对该方案和算法进行了理论分析及实验验证,结果表明该文所提出的方案和算法具有较高的响应速度、准确率及用户满意度.
It is one of important topics in social network research how to get the user＇ s behavior feature and discover actively potential social relations by automatic context-aware. This paper presents a context-aware mobile P2P social network framework, aggregation model and the discovery algorithm. The user＇s location information, environmental characteristics etc. are introduced to the aggregate algorithm, which aggregate intelligently to potential P2P social network and discover the suited relationship according to user＇s demand. Thereby, the social blindness and randomness are avoi- ded. The theoretical analysis and experimental results show that the proposed approach and the algorithm have a higher response speed, accuracy and user＇s satisfaction.
出处
《计算机学报》
EI
CSCD
北大核心
2012年第6期1223-1234,共12页
Chinese Journal of Computers
基金
国家自然科学基金(61103198
61100112
60970143)
教育部科学技术重点项目基金(109016)
教育部人文社会科学研究青年基金(11YJCZH006)
中央财经大学学科建设基金(CUFEIE201107)资助~~
