A New Multi-Wave Cellular Learning Automata and Its Application for Link Prediction Problem in Social Networks

الموضوعات : Journal of Computer & Robotics

Mozhdeh Khaksar Manshad ¹ (Department of Computer Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran)
Mohammad Reza Meybodi ² (Amirkabir University of Technology, Tehran, Iran)
Afshin Salajegheh ³ (Department of Computer Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran)

تاريخ الإرسال : 24 السبت , شوال, 1442 تاريخ التأكيد : 21 الخميس , ذو القعدة, 1442 تاريخ الإصدار : 20 الثلاثاء , شوال, 1442

الکلمات المفتاحية: Cellular Learning Automata, Social networks, Link Prediction problem,

ملخص المقالة :

Link Prediction (LP) is one of the main research areas in Social Network Analysis (SNA). The problem of LP can help us understand the evolution mechanism of social networks, and it can be used in different applications such as recommendation systems, bioinformatics, and marketing. Social networks can be shown as a graph, and LP algorithms predict future connections by using previous network information. In this paper, a multi-wave cellular learning automaton (MWCLA) is introduced and used to solve the LP problem in social networks. The proposed model is a new CLA with a connected structure and a module of LAs in each cell where a cell module’s neighbors are its successors. In the MWCLA method for improving convergence speed and accuracy, multiple waves have been used parallelly in the network. By using multiple waves, different information of the network can be considered for predicting links in the social network. Here we show that the model converges upon a stable and compatible configuration. Then for the LP problem, it has been demonstrated that MWCLA produces much better results than other approaches compared to some state-of-the-art methods.

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