Abstract
Community detection is an important topic in complex network analysis which can explore valuable relationships in the networks, such as protein-protein interactions, advertisement recommendations, etc. Recently, the structure and attributes of a network are expected to be integrated to obtain a more accurate community division. But existing community detection algorithms based on multiobjective optimization evolutionary algorithms (MOEAs) for attributed networks have two common problems. First, their encoding strategies completely depend on the network structure, which limits their use of attribute information in search. Second, the calculation of the attribute objective function is time-consuming. In this paper, we propose a novel algorithm that combines the nodes’ embedding vectors generated by a Skip-Gram model with an attention-based multiobjective optimization evolutionary algorithm to discover overlapping communities on networks with attributes. With the help of embedding vectors, the attention-based encoding strategy can overcome the problem of the limited searching capability of traditional MOEAs’ encoding schemes that depend only on a network structure, and an attribute objective function based on embedding vectors is designed which can be calculated in linear time to improve the computational efficiency. The statistical results in artificial and real-world networks demonstrate the feasibility and effectiveness of the proposed method.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China under Grant No. 61672159, No. 61672158, No. 61300104 and No. 62002063, the Fujian Collaborative Innovation Center for Big Data Applications in Governments, the Fujian Industry-Academy Cooperation Project under Grant No. 2017H6008 and No. 2018H6010, the Natural Science Foundation of Fujian Province under Grant No. 2018J07005, No. 2019J01835 and No. 2020J05112, the Fujian Provincial Department of Education under Grant No. JAT190026, the Fuzhou University under Grant 510872/GXRC-20016 and Haixi Government Big Data Application Cooperative Innovation Center.
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Lin, X., Chen, Z., Guo, K., Chen, Y. (2022). An Attention-Based Multiobjective Optimization Evolutionary Algorithm for Community Detection in Attributed Networks. In: Sun, Y., et al. Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2021. Communications in Computer and Information Science, vol 1491. Springer, Singapore. https://doi.org/10.1007/978-981-19-4546-5_22
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DOI: https://doi.org/10.1007/978-981-19-4546-5_22
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