首页> 外文会议>2013 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications >Determining Similar Recommenders Using Improved Collaborative Filtering in MANETs
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Determining Similar Recommenders Using Improved Collaborative Filtering in MANETs

机译:在MANET中使用改进的协同过滤确定类似的推荐人

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摘要

In a MANET environment, recommendation systems face a significant challenge whilst dealing with mobile nodes. Specifically, when a "node" is about to join a new cluster it may require some form of reference from a previously associated cluster. As such, research in this area has primarily focused on the selection of recommender nodes so that the overall consistency of the MANET system is maintained. In this study, an improved collaborative filtering mechanism has been exploited to address the selection of a group of suitable recommenders. First, a cluster formation algorithm has been used to group the set of recommenders based on their similarity measures with predictions computed independently for each cluster. Next, a threshold window is identified for selecting the best group of similar recommenders eliminating the lowest and highest trusted recommenders. Simulation results suggest that the proposed trust based similarity measures can greatly enhance the accuracy of node based trust management scheme.
机译:在MANET环境中,推荐系统在处理移动节点时面临巨大挑战。具体地,当“节点”将要加入新集群时,它可能需要来自先前关联的集群的某种形式的引用。因此,该领域的研究主要集中在推荐节点的选择上,以便维护MANET系统的整体一致性。在这项研究中,已开发出一种改进的协作过滤机制来解决一组合适的推荐者的选择。首先,已经使用聚类形成算法将推荐者集合基于其相似性度量与针对每个聚类独立计算的预测进行分组。接下来,确定阈值窗口,以选择相似推荐者的最佳组,从而消除最低和最高可信推荐者。仿真结果表明,所提出的基于信任度的相似性度量可以大大提高基于节点的信任度管理方案的准确性。

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