This study is aiming at the central challenge for network analysis and application of how to identify key nodes in hypernetwork representations. Although there are many measuring methods based on traditional network, most of them use single criteria, which is often confronted with the problem of incomplete or inaccurate information on the structure of hyper network. In this study, a new multi-criteria measuring method with adjustable parameters is proposed, which takes the node degree, star degree and betweenness into considerations. According to the experimental results with a numerical example of hypernetwork, our method shows good performance on discrimination and precision to evaluate the importance of nodes as compared with several existing measuring methods for nodes in traditional network.
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