DSMN: A New Approach for Link Prediction in Multilplex Networks
Publish place: International Journal of Information and Communication Technology Research (IJICT، Vol: 14، Issue: 3
Publish Year: 1401
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_ITRC-14-3_003
تاریخ نمایه سازی: 1 آبان 1401
Abstract:
In a multiplex network, there exists different types of relationships between the same set of nodes such as people which have different accounts in online social networks. Previous researches have proved that in a multiplex network the structural features of different layers are interrelated. Therefore, effective use of information from other layers can improve link prediction accuracy in a specific layer. In this paper, we propose a new inter-layer similarity metric DSMN, for predicting missing links in multiplex networks. We then combine this metric with a strong intra-layer similarity metric to enhance the performance of link prediction. The efficiency of our proposed method has been evaluated on both real-world and synthetic networks and the experimental results indicate the outperformance of the proposed method in terms of prediction accuracy in comparison with similar methods.
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Authors
Samira Rafiee Samira Rafiee
Department of Computer Engineering University of Kurdistan Sanandaj, Iran
Alireza Abdollahpouri
Department of Computer Engineering University of Kurdistan Sanandaj, Iran