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How Hypergraph-to-Graph Conversion Affects Cooperative Working Visualization: A Multi-metric Evaluation

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Computer Supported Cooperative Work and Social Computing (ChineseCSCW 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2012))

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Abstract

It is commonplace to use hypergraphs to represent cooperative work since hypergraphs explicitly capture complex interactions and connections, enabling researchers to analyze with ease. Nonetheless, hypergraphs are usually chaotic due to sophisticated relations between vertices. Therefore, it is necessary to look into which method prevails over other methods in specific circumstances. In our study, we propose an appraisal framework in which we use six quantitative and five qualitative metrics to assess the performance of each conversion method in terms of layout quality and effectiveness. The results show that while no method is ideal for all situations, certain methods, such as Centroid-single, perform well. Researchers can use our experiment results to select the optimal method tailored to their specific dataset and circumstances. This paper serves researchers and practitioners in choosing the most suitable conversion method for their research.

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Acknowledgement

This work was supported in part by the Open Foundation of the Key lab (center) of Anhui Province Key Laboratory of Intelligent Building & Building Energy Saving (IBES2022KF03), and the Scientific and Technological Achievement Cultivation Project of Intelligent Manufacturing Institute of HFUT (IMIPY2021022).

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Authors and Affiliations

  1. Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology), Ministry of Education, Hefei, 230009, China

    Zhihan Xiong, Ruixin Mu, Chongshen Yang, Wenjun Xie & Qiang Lu

  2. School of Software, Hefei University of Technology, Hefei, 230601, China

    Zhihan Xiong, Ruixin Mu, Chongshen Yang & Wenjun Xie

  3. Intelligent Interconnected Systems Laboratory of Anhui Province (Hefei University of Technology), Hefei, 230009, China

    Zhihan Xiong, Ruixin Mu, Chongshen Yang, Wenjun Xie & Qiang Lu

  4. School of Computer and Information, Hefei University of Technology, Hefei, 230601, China

    Qiang Lu

Authors
  1. Zhihan Xiong
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  2. Ruixin Mu
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  3. Chongshen Yang
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  4. Wenjun Xie
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  5. Qiang Lu
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Corresponding author

Correspondence to Qiang Lu .

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Editors and Affiliations

  1. Shandong University, Jinan, China

    Yuqing Sun

  2. Fudan University, Shanghai, China

    Tun Lu

  3. Harbin Engineering University, Harbin, China

    Tong Wang

  4. Tongji University, Shanghai, China

    Hongfei Fan

  5. Guangdong University of Technology, Guangzhou, China

    Dongning Liu

  6. Tongji University, Shanghai, China

    Bowen Du

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Xiong, Z., Mu, R., Yang, C., Xie, W., Lu, Q. (2024). How Hypergraph-to-Graph Conversion Affects Cooperative Working Visualization: A Multi-metric Evaluation. In: Sun, Y., Lu, T., Wang, T., Fan, H., Liu, D., Du, B. (eds) Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2023. Communications in Computer and Information Science, vol 2012. Springer, Singapore. https://doi.org/10.1007/978-981-99-9637-7_15

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  • DOI: https://doi.org/10.1007/978-981-99-9637-7_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-9636-0

  • Online ISBN: 978-981-99-9637-7

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