[ESWA 119775] A novel network core structure extraction algorithm utilized variational autoencoder for community detection

Description

We use two example datasets, karate and dolphins, where the csv file with "adj" represents the adjacency matrix and the csv file with "real" represents the real community division of each node, which can be directly used as input to the CSEA algorithm.

Steps to reproduce

Using the "adj" and "real" files of the same dataset as input to the CSEA algorithm, follow the steps in https://github.com/PeterWana/CSEA to obtain the algorithm's output results.

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Funders

• National Natural Science Foundation of China

  China

  Grant ID: 62120106011
• Shaanxi Science and Technology Department

  China

  Grant ID: 2021JM-347
• Shaanxi Provincial Department of education Special project

  Grant ID: No. 21JC026

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