An efficient percolation-based method for influence maximization problem
Publish Year: 1399
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
DCBDP06_073
تاریخ نمایه سازی: 25 اسفند 1399
Abstract:
Identification of influential nodes is one of the important aspects of social network analysis. These nodes are used for maximizing influence in many applications. Since Influence maximization is an NP-Hard problem, many other greedy and heuristic methods have been proposed in recentdecades to find near optimal seed nodes in large-scale data. However, they have challenges such as time complexity, accuracy, and efficiency. This paper offers a new percolationbased node selection method for influence maximization problem that is called PBN algorithm. This method selectsinfluential nodes based on the percolation, weighting, and removing approach in social networks. Experimental results show that the proposed algorithm outperforms other compared algorithms such as LIR, ProbDegree, and K-core in terms of influence spread with acceptable time-complexity.
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Authors
Hamid Ahmadi Beni
Dept. of Computer Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran
Sevda Azimi
Dept. of Computer Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran
Asgarali Bouyer
Dept. of Computer Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran