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Research on Dynamic Community Detection Method Based on Multi-dimensional Feature Information of Community Network

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Trends and Applications in Knowledge Discovery and Data Mining (PAKDD 2024)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14658))

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Abstract

With the continuous development of technology, we have the ability to fully record all aspects of data information of every individual in the society, so how to utilize this information to create greater value is becoming more and more important. Compared with the traditional static community detection, the study of dynamic community detection is more in line with the real situation in the society. Thus, in this paper, a method that can utilize the information of diversified dynamic community networks is proposed, i.e., Dynamic Community Detection Method based on Multidimensional Feature Information of Community (Dcdmf), which utilizes neural networks with strong learning and adaptive capabilities, the ability to automatically extract useful features and process complex data, and the ability to process the graph nodes and the data between the nodes of the dynamic community network, and the ability to real-time adjust the current community representation data based on historical information, and record the current community representation data for the next moment of community data. The experimental results in the paper show that the method has a certain degree of effectiveness.

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Acknowledgments

This work was supported in part by the National Science Foundation of China (62272311), National Key R & D Program of China (2018YFC0831005), Science and Technology Support project of Tianjin Eco-City of China (STCKJ2020-WRJ), and Finance science and technology project of the 12th Division of Xinjiang Construction Corps of China (SR202103).

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Authors and Affiliations

  1. School of Computer Science and Technology, Xinjiang University, Urumqi, 830017, China

    Kui Hu & Zhenyu Zhang

  2. Xinjiang Key Laboratory of Multilingual Information Technology, Urumqi, 830017, China

    Zhenyu Zhang

  3. College of International Business, Zhejiang Yuexiu University, Shaoxing, China

    Xiaoming Li

Authors
  1. Kui Hu
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  2. Zhenyu Zhang
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  3. Xiaoming Li
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Correspondence to Kui Hu .

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Editors and Affiliations

  1. Singapore Management University, Singapore, Singapore

    Zhaoxia Wang

  2. Monash University, Clayton, VIC, Australia

    Chang Wei Tan

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Hu, K., Zhang, Z., Li, X. (2024). Research on Dynamic Community Detection Method Based on Multi-dimensional Feature Information of Community Network. In: Wang, Z., Tan, C.W. (eds) Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2024. Lecture Notes in Computer Science(), vol 14658. Springer, Singapore. https://doi.org/10.1007/978-981-97-2650-9_4

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  • DOI: https://doi.org/10.1007/978-981-97-2650-9_4

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  • Online ISBN: 978-981-97-2650-9

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