计算机科学
最大化
维数(图论)
启发式
数学优化
方案(数学)
扩散
时间预算
效用最大化
人工智能
数学
数理经济学
生物
热力学
物理
生态学
数学分析
纯数学
作者
Qiang He,Xingwei Wang,Min Huang,Yuliang Cai,Chuangchuang Zhang,Lianbo Ma
摘要
Summary To synthetically and dynamically make strategic choices in social networks, a novel adaptive approach to deal with two‐dimension influence maximization problem (TIMP) is proposed with game‐based diffusion model, which can achieve trade‐off between diffusion time and the number of active nodes. At first, TIMP model is synthetically formulated, and diffusion time and the number of active nodes are defined mathematically. In particular, budget efficiency is presented to describe TIMP in order that an appropriate trade‐off between diffusion time and the number of active nodes can be reached. Then, an adaptive heuristic (A‐Heuristic) scheme is proposed to dynamically determine the initial seed nodes (ie, the most influential nodes). Finally, experiments are performed, and their results verify the superior performance of the proposed scheme in terms of budget efficiency, running time, and the number of active nodes.
科研通智能强力驱动
Strongly Powered by AbleSci AI