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

Journal of Computer & Robotics

دوره 14، شماره 1 - شماره پیاپی 23، شهریور 2021، صفحه 1-20   

نویسندگان

Mozhdeh Khaksar Manshad^{* 1}؛ Mohammad Reza Meybodi²؛ Afshin Salajegheh¹

¹Department of Computer Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

²Amirkabir University of Technology, Tehran, Iran

چکیده

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.

کلیدواژه‌ها

Social Networks؛ Cellular Learning Automata؛ Link Prediction problem

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