Most Influential Node Selection in Social Network using Genetic Algorithm

被引：0

作者：

Roy, Mithun ^{[1
]}

Pan, Indrajit ^{[2
]}

机构：

[1] Siliguri Inst Technol, Dept Comp Sci & Engn, Siliguri, W Bengal, India

[2] RCC Inst Informat Technol, Dept Informat Technol, Kolkata, W Bengal, India

来源：

2018 FOURTH IEEE INTERNATIONAL CONFERENCE ON RESEARCH IN COMPUTATIONAL INTELLIGENCE AND COMMUNICATION NETWORKS (ICRCICN) | 2018年

关键词：

DiffusedGreedy Algorithm; Genetic Algorithm; Influence Maximization; Social Networks;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Goal of Influence Maximization problem is to find a top-k powerful nodes as a seed set which has a maximum influence with respect to a propagation model. This is NP-hard in nature. Most of the related algorithms are based on greedy methods, which are computationally expensive. Any exhaustive search algorithm can't discover the good solution in a sensible time. In this paper we introduce a performance oriented algorithm for solving the influence maximization problem using Greedy inspired Genetic Algorithm. We have observed that the performance of proposed algorithm is outperforming similar existing algorithms for maximizing influence Spread.

引用

页码：214 / 220

页数：7

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