社交网络中基于模糊判定的固定信息推荐算法研究

Research on Algorithm of Fixed Information Recommendation in Social Networks Based on Fuzzy Identification

社交网络是一种无现实限制的全天候信息交互网络,社交网络的固定信息推荐是保证网络安全,评估网络用户信任度和实现隐私保护的基础。社交网络的固定信息具有多主体性和随机性特点,难以实现有效的信息推荐。传统的社交网络固定信息推荐算法采用主体协商的云信任数据推荐,对社交网络的非常态固定信息推荐的主观性较大,性能不好。提出一种基于模糊判定的社交网络中固定信息推荐算法。构建社交网络固定信息特征提取模型,采用网格划分技术对路由结点所在的平面区域进行特征划分,对固定信息进行模糊跟踪判定,得到社交网络中固定信息自适应跟踪概率分布,实现固定信息推荐算法改进。仿真实验表明,该算法能有效提高社交网络中固定信息推荐准确投递率。对节点缓存依赖性较弱,网络开销比较稳定,性能优越。

A social network is an all-weather information interaction network has no realistic restrictions, fixed information recommendation in social networks is to guarantee network security, user trust evaluation based on network degree and achieve privacy protection. Fixed information social network has more subjectivity and randomness characteristics, and it is difficult to achieve effective information recommendation. Cloud trust data of traditional social network information recommendation algorithm uses fixed agent negotiation recommendation on social networks difficult state fixed information recommendation is larger, the performance is not good. Put forward a kind of fixed information recommendation algorithm based on fuzzy decision in a social network. To build a social network of fixed information feature extraction model, the fixed information fuzzy tracking decision, get the stationary probability distribution information of adaptive tracking in a social network, the realization of fixed information recommendation algorithm improvement. Simulation results show that the algorithm can effectively improve the social network information recommendation and accurate delivery rate fixed. The nodes cache dependency is weak, the network overhead is relatively stable, it has superior performance.