Protein–protein interactions form a network where nodes denote proteins and edges denote interactions among them. Treating individuals as nodes for example, and associations between corresponding persons as edges, social relations could be abstracted as a network. A typical network consists of nodes and edges, where nodes denote various entities in real systems and edges represent the relationships between entities. Networks are a natural and powerful tool for characterizing a large number of social, biological, and information systems composed of interacting elements, and network science is one of the most active interdisciplinary fields of research today. With the development of network analysis, many complex systems can be described as networks. We further analyze the results of experiments in detail, aiming to discover the most suitable approach for each kind of network. Moreover, we analyze thirty-six datasets and divide them into seven types of networks according to their topological features shown in real networks and perform comprehensive experiments on these networks. The network embedding-based methods, especially graph neural network-based methods, which have attracted increasing attention in recent years, have been creatively investigated as well. In this work, a new taxonomy is proposed to divide the link prediction methods into five categories and a comprehensive overview of these methods is provided. There are a variety of techniques for link prediction based on the topology of the network and the properties of entities. Therefore, it is extremely important to study the link prediction problem on complex networks. Link prediction plays an important role in complex network analysis in that it can find missing links or predict the links which will arise in the future in the network by analyzing the existing network structures. The outbreak of COVID-19 has had a huge impact on various complex networks in the real world, for example global trade networks, air transport networks, and even social networks, known as racial equality issues caused by the spread of the epidemic. ![]() Complex networks have been used widely to model a large number of relationships.
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