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Utilizing Tags for Scientific Workflow Recommendation

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International Conference on Applications and Techniques in Cyber Intelligence ATCI 2019 (ATCI 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1017))

Abstract

Scientific workflow recommendation is playing increasingly important role, as an increasing number of reusable scientific workflow are published and shared on the Web. This paper proposes a scientific workflow recommendation method to promote the reuse of workflow. We utilize tags for recommending workflows. The similarity of workflows is obtained by tags besides the workflow descriptions, structures, and hierarchies. Based on the similarities of workflows, the workflows are clustered and recommended. The experimental results show that our method is effective and accurate for recommending workflows.

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Acknowledgment

The work described in this paper was supported by the National Natural Science Foundation of China (No. 61772193), Hunan Provincial Natural Science Foundation of China (No. 2017JJ4036, 2018JJ2139), Innovation Platform Open Foundation of Hunan Provincial Education Department under Project (No.17K033) and Scientific Research Fund of Hunan Provincial Education Department (No. 17C0644, 18C1470, 14B058).

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Authors and Affiliations

  1. School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, China

    Junjie Hou & Yiping Wen

  2. Key Laboratory of Knowledge Processing and Networked Manufacturing, Hunan University of Science and Technology, Xiangtan, China

    Yiping Wen

Authors
  1. Junjie Hou
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  2. Yiping Wen
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Corresponding author

Correspondence to Yiping Wen .

Editor information

Editors and Affiliations

  1. Faculty of Science, Deakin University, Geelong, VIC, Australia

    Jemal H. Abawajy

  2. Department of Information Systems and Cyber Security, The University of Texas at San Antonio, San Antonio, TX, USA

    Kim-Kwang Raymond Choo

  3. School of Computing and Mathematics, Charles Sturt University, Albury, NSW, Australia

    Rafiqul Islam

  4. Shanghai University, Shanghai, China

    Zheng Xu

  5. School of Computer Science, University of Oklahoma, Norman, OK, USA

    Mohammed Atiquzzaman

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Hou, J., Wen, Y. (2020). Utilizing Tags for Scientific Workflow Recommendation. In: Abawajy, J., Choo, KK., Islam, R., Xu, Z., Atiquzzaman, M. (eds) International Conference on Applications and Techniques in Cyber Intelligence ATCI 2019. ATCI 2019. Advances in Intelligent Systems and Computing, vol 1017. Springer, Cham. https://doi.org/10.1007/978-3-030-25128-4_117

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