Weighted estimation of information diffusion probabilities for independent cascade model 机翻标题: 暂无翻译,请尝试点击翻译按钮。

会议集名/来源
2018 4th International Conference on Web Research: ICWR 2018, Tehran, Iran, 25-26 April 2018
出版年
2018
页码
63-69
会议地点
Tehran
语种
eng
作者单位
Computer Engineering and Information Technology Department, Amirkabir University of Technology, Tehran, Iran;Computer Engineering and Information Technology Department, Amirkabir University of Technology, Tehran, Iran;School of Computer Science, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
作者
Yoosof Mashayekhi;Mohammad Reza Meybodi;Alireza Rezvanian
摘要
In recent years, social networks have become popular among Internet users, and various studies have been performed on analysis of such networks. One of the important issues in analyzing social networks is information diffusion analysis. In this context, users' behavior is assumed to be influenced by other social network users. Several models have been designed to simulate and analyze how information is disseminated in social networks. In this paper, we study the problem of learning the diffusion probabilities for the independent cascade model. We first outline the importance of the subject, and then we propose a method to estimate diffusion probabilities. In this method, we assign a weight to each individual diffusion sample of each link in the network based on its parameters. We propose two weighting schemes to consider the different effects of diffusion samples. Then, we evaluate our method for learning diffusion probabilities with the help of several datasets and present the results. Also, the method presented in this paper is compared with other methods in terms of mean absolute error and training time.
机翻摘要
暂无翻译结果,您可以尝试点击头部的翻译按钮。
关键词
Social network services;Computational modeling;Diffusion processes;Feature extraction;Analytical models;Estimation;Training
若您需要申请原文,请登录。

最新评论

暂无评论。

登录后可以发表评论


意见反馈
返回顶部