摘要
为了提高个性化PageRank算法在大型网络图中的计算效率,提出基于可达查询的PPR算法。该算法采用一定的分割方法将大图上的计算转移到子图上,通过可达查询算法快速删除所有与计算无关的节点与边,得到源节点的可达子图,在可达子图上计算节点的近似PPR估计值。实验结果证明,该算法可显著提高PPR的计算效率。
In order to improve the computing efficiency of personalized PageRank algorithm in large network graph,PRR algorithm based on accessible query is proposed.The main idea of the algorithm is to transfer the calculation on the large graph to the subgraph by using a certain segmentation method.The computational process is as follows:firstly,the accessible subgraph of the source node is obtained by quickly deleting all the nodes and edges that are not related to the computations through the reachable query algorithm,then the approximate PPR estimates of nodes are calculated on the accessible subgraph.The experimental results show that the proposed algorithm can significantly improve the computational efficiency of PPR.
作者
贾瑞娜
张向利
闫坤
张红梅
JIA Ruina;ZHANG Xiangli;YAN Kun;ZHANG Hongmei(School of Information and Communication,Guilin University of Electronic Technology,Guilin 541004,China)
出处
《桂林电子科技大学学报》
2020年第1期39-43,共5页
Journal of Guilin University of Electronic Technology
基金
国家自然科学基金(61461010,61363031)
广西研究生教育创新计划(2017YJCX22)。