级联
最大化
阈值模型
次模集函数
计算机科学
光学(聚焦)
扩散
线性模型
数学优化
数学
机器学习
工程类
物理
化学工程
热力学
光学
作者
Paulo Shakarian,Abhinav Bhatnagar,Ashkan Aleali,Elham Shaabani,Ruocheng Guo
出处
期刊:SpringerBriefs in computer science
日期:2015-01-01
卷期号:: 35-48
被引量:34
标识
DOI:10.1007/978-3-319-23105-1_4
摘要
In this chapter, we focus on perhaps the two most prevalent diffusion models in computer science—the independent cascade and linear threshold models. We describe different properties of these models and how these properties affect solving problems such as influence maximization and influence spread. We describe approaches to address influence maximization problem in independent cascade model and linear threshold model that rely on the maximization of submodular functions—as well as extensions to these approaches for larger datasets.
科研通智能强力驱动
Strongly Powered by AbleSci AI