Proximity-Aware Degree-Based Heuristics for the Influence Maximization Problem

Computer and Knowledge Engineering

مقاله 4، دوره 5، شماره 1 - شماره پیاپی 9، تیر 2022، صفحه 37-46   

نوع مقاله: Semantic Technology-Kahani

شناسه دیجیتال (DOI): 10.22067/cke.2022.63265.0

نویسندگان

Maryam Adineh؛ Mostafa Nouri Baygi^*

Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.

چکیده

The problem of influence maximization is selecting the most influential individuals in a social network. With the popularity of social network sites and the development of viral marketing, the importance of the problem has increased. The influence maximization problem is NP-hard, and therefore, there will not exist any polynomial-time algorithm to solve the problem unless P = NP. Many heuristics are proposed for finding a nearly good solution in a shorter time. This study proposes two heuristic algorithms for finding good solutions. The heuristics are based on two ideas: 1) vertices of high degree have more influence in the network, and 2) nearby vertices influence on almost analogous sets of vertices. We evaluate our algorithms on several well-known data sets and show that our heuristics achieve better results (up to 15% in the influence spread) for this problem in a shorter time (up to 85% improvement in the running time).

کلیدواژه‌ها

Degree centrality؛ Heuristic algorithm؛ Independent cascade model؛ Influence maximization