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Frequent Closed Subgraph Mining: A Multi-thread Approach

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Intelligent Information and Database Systems (ACIIDS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13757))

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Abstract

Frequent subgraph mining (FSM) is an interesting research field and has attracted a lot of attention from many researchers in recent years, in which closed subgraph mining is a new topic with many practical applications. In the field of graph mining, GraMi (GRAph MIning) is considered state-of-the-art, and many algorithms have been developed based on the improvement of this approach. In 2021, we proposed the CloGraMi algorithm based on GraMi to mine closed frequent subgraphs from a large graph rapidly and efficiently. However, with NP time complexity and extremely high cost in terms of running time, graph mining is always a challenging problem for all researchers. In this paper, we propose a parallel processing strategy aiming to improve the execution speed of our CloGraMi algorithm. Our experiments on six datasets, including both undirected and directed graphs, with different sizes, including large, medium and small, show that the new algorithm significantly reduces running time and improves performance, and has better performance compared to the original algorithm.

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Acknowledgement

This work was supported by Institute for Computational Science and Technology (ICST) – Ho Chi Minh City and the Department of Science and Technology (DOST) – Ho Chi Minh City under grant no. 23/2021/HĐ-QKHCN.

Author information

Authors and Affiliations

  1. Faculty of Information and Communications, Kien Giang University, Kien Giang, Vietnam

    Lam B. Q. Nguyen

  2. Faculty of Information Technology, HUTECH University, Ho Chi Minh City, Vietnam

    Ngoc-Thao Le & Bay Vo

  3. Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland

    Hung Son Nguyen

  4. Institute for Computational Science and Technology (ICST), Ho Chi Minh City, Vietnam

    Tri Pham

Authors
  1. Lam B. Q. Nguyen
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  2. Ngoc-Thao Le
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  3. Hung Son Nguyen
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  4. Tri Pham
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  5. Bay Vo
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Corresponding author

Correspondence to Bay Vo .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Vietnam National University, Ho Chi Minh City, Ho Chi Minh City, Vietnam

    Tien Khoa Tran

  3. Al-Farabi Kazakh National University, Almaty, Kazakhstan

    Ualsher Tukayev

  4. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

  6. University of Newcastle, Newcastle, NSW, Australia

    Edward Szczerbicki

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Nguyen, L.B.Q., Le, NT., Nguyen, H.S., Pham, T., Vo, B. (2022). Frequent Closed Subgraph Mining: A Multi-thread Approach. In: Nguyen, N.T., Tran, T.K., Tukayev, U., Hong, TP., Trawiński, B., Szczerbicki, E. (eds) Intelligent Information and Database Systems. ACIIDS 2022. Lecture Notes in Computer Science(), vol 13757. Springer, Cham. https://doi.org/10.1007/978-3-031-21743-2_6

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  • DOI: https://doi.org/10.1007/978-3-031-21743-2_6

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  • Online ISBN: 978-3-031-21743-2

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