Combined Estimating Influence Probabilities for an Influence Maximization Problem in Social Networks and Its Application in the Power Industry
Subject Areas : Computer Engineering and ITSohameh Mohammadi 1 , .Mohammad H Nadimi-Shahraki 2 , Zahra Beheshti 3 , kamran zamanifar 4
1 - Department of Computer Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
2 - Islamic Azad University of Najafabad & Torrens University Australia
3 - دانشکده مهندسی کامپیوتر- واحد نجف آباد، دانشگاه آزاد اسلامی، نجف آباد، ایران
4 - Kamran Zamanifar Department of Computer Engineering,University of Isfahan Isfahan, Iran
Keywords: Social networks, influence maximization, information diffusion modeling, influence Probabilities,
Abstract :
Nowadays, online social networks have an inseparable connection with the daily life of many people in the world. The applications of social networks are increasing in businesses for advertising, marketing, and recommender systems, as well as in resource and energy consumption management systems. One of the most important problems in the information diffusion process of social networks is the influence maximization. In recent years, some research has been conducted to improve the prediction quality of information diffusion models in this problem. In a review of existing models, the influence probabilities among users are estimated unrealistically. In this research, a new method has been proposed to determine the influence probabilities among social network users. This method is a combination of two main approaches in the calculation of influence probabilities, including the use of an action log table and the uniform method with a predetermined value. The performance of the proposed method was evaluated and compared with competitive methods on different real-world social network data sets. The results of the experiments show that the proposed method can increase the efficiency of the predictions in solving the influence maximization problems.
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