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| A Multi-attribute Decision-making Method Based on Entropy to Identify Important Nodes in Hypernetworks |
| WU Yinghan, LI Mingda, HU Feng
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| a. The State Key Laboratory of Tibetan Intelligent Information Processing and Application; b. Academy of Plateau Science and Sustainability, Qinghai Normal University, Xining 810008, China |
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Abstract In order to overcome the deficiency of incomplete importance of nodes evaluated by single attribute and subjective weight selection of indicators, based on the K-shell method in hypernetwork, this paper introduces the influence of neighbor nodes on their own nodes while comprehensively considering the attributes of nodes, combined with the index of betweenness centrality, using the entropy method to determine the contribution weight of each index to node importance. A method to identify important nodes in hypernetworks is proposed from both local and global perspectives. The advantages and disadvantages of different identification methods are compared through the natural connectivity of network and the relative size of the maximum connected subgraph, and the empirical data of Xining city bus hypernetwork is used to further verify the effectiveness a feasibility of the proposed method.
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Received: 01 August 2022
Published: 28 December 2023
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