Random walk-based algorithm for distance-aware influence maximization on multiple query locations

作者：

Highlights：

• The problem of distance-aware influence maximization on multiple query locations is defined.

• An algorithm is presented to estimate the nodes’ upper and lower bounds of influence spreading based on a set of anchor points.

• An algorithm is proposed to select the anchor points by partitioning the nodes into groups.

• We propose an algorithm to analyze the paths of influence spreading and get an estimation of each node’s influence spreading.

• A greedy-based algorithm is presented to detect the seeds. Pruning technique is used to accelerate processing the queries.

摘要

•The problem of distance-aware influence maximization on multiple query locations is defined.•An algorithm is presented to estimate the nodes’ upper and lower bounds of influence spreading based on a set of anchor points.•An algorithm is proposed to select the anchor points by partitioning the nodes into groups.•We propose an algorithm to analyze the paths of influence spreading and get an estimation of each node’s influence spreading.•A greedy-based algorithm is presented to detect the seeds. Pruning technique is used to accelerate processing the queries.

论文关键词：Distance-aware,Influence maximization,Random walk,Greedy method

论文评审过程：Received 5 May 2021, Revised 10 April 2022, Accepted 12 April 2022, Available online 28 April 2022, Version of Record 14 May 2022.

论文官网地址：https://doi.org/10.1016/j.knosys.2022.108820