计算机工程 ›› 2019, Vol. 45 ›› Issue (3): 182-187.doi: 10.19678/j.issn.1000-3428.0049326

• 人工智能及识别技术 • 上一篇    下一篇

信任社交网络中改进的物质扩散推荐算法

蔡永嘉,李冠宇   

  1. 大连海事大学 信息科学技术学院,辽宁 大连 116026
  • 收稿日期:2017-11-16 出版日期:2019-03-15 发布日期:2019-03-15
  • 作者简介:蔡永嘉(1995—),男,硕士研究生,主研方向为智能信息处理;李冠宇,教授、博士、博士生导师。
  • 基金项目:

    国家自然科学基金(61371090)。

Improved Mass Diffusion Recommendation Algorithm in Trusted Social Network

CAI Yongjia,LI Guanyu   

  1. Faculty of Information Science and Technology,Dalian Maritime University,Dalian,Liaoning 116026,China
  • Received:2017-11-16 Online:2019-03-15 Published:2019-03-15

摘要:

传统物质扩散推荐算法多样性低且未考虑用户所处的社交网络信息和物品的受欢迎程度。为此,在基于信任机制的社交网络中,提出一种改进的物质扩散推荐算法。引入信任机制形成目标用户的最优邻居集,模拟用户-物品二分网络,根据用户信任度对物品初始资源进行分配。考虑物品双向扩散能力并结合物品流行度的可调参数,实现资源再分配,从而优化目标用户的推荐结果。在真实数据集上的实验结果表明,该算法能在保证较高推荐准确率的同时,增强推荐结果的多样性。

关键词: 物质扩散, 信任机制, 社交网络, 流行度, 二分网络

Abstract:

Traditional mass diffusion recommendation algorithm has low diversity and its neglection to user’s social network information and object popularity.Therefore,this paper proposes a mass diffusion recommendation algorithm based on trust mechanism in social network.The trust mechanism is introduced to form an optimal neighbor set for target user.By simulating on the user-object bipartite network,the initial object resources are reallocated according to trust mechanism.The object’s bidirectional diffusion is taken into consideration,and some tunable parameters of object popularity are introduced to achieve resource redistribution,so that the better recommendation results for the target users can be gotten.Experimental results on real-world data sets reveal that the algorithm can enhance the diversity of recommendation results while ensuring higher recommendation accuracy.

Key words: mass diffusion, trust mechanism, social network, popularity, bipartite network

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