Link Prediction in Multiplex Networks based on Interlayer Similarity

Abstract

Some networked systems can be better modelled by multilayer structure where the individual nodes develop relationships in multiple layers. Multilayer networks with similar nodes across layers are also known as multiplex networks. This manuscript proposes a novel framework for predicting forthcoming or missing links in multiplex networks. The link prediction problem in multiplex networks is how to predict links in one of the layers, taking into account the structural information of other layers. The proposed link prediction framework is based on interlayer similarity and proximity-based features extracted from the layer for which the link prediction is considered. To this end, commonly used proximity-based features such as Adamic-Adar and Jaccard Coefficient are considered. These features that have been originally proposed to predict missing links in monolayer networks, do not require learning, and thus are simple to compute. The proposed method introduces a systematic approach to take into account interlayer similarity for the link prediction purpose. Experimental results on both synthetic and real multiplex networks reveal the effectiveness of the proposed method and show its superior performance than state-of-the-art algorithms proposed for the link prediction problem in multiplex networks.

References in corpus (14)

• Multilayer Networks
• Link Prediction in Complex Networks: A Survey
• Hierarchical structure and the prediction of missing links in networks
• Clustering and preferential attachment in growing networks
• Predicting Missing Links via Local Information
• Recommender Systems
• Missing and spurious interactions and the reconstruction of complex networks
• Structural measures for multiplex networks
• The physics of spreading processes in multilayer networks
• Emergence of network features from multiplexity
• Degree mixing in multilayer networks impedes the evolution of cooperation
• Spreading processes in Multilayer Networks
• Multiple routes transmitted epidemics on multiplex networks
• A probabilistic model to resolve diversity-accuracy challenge of recommendation systems

Cited by in corpus (4)

• Prediction of scientific collaborations through multiplex interaction networks
• Link prediction in multiplex networks via triadic closure
• SimBins: An information-theoretic approach to link prediction in real multiplex networks
• Providing a Link Prediction Model based on Structural and Homophily Similarity in Social Networks