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    A Survey of Human-Centered Evaluations in Human-Centered Machine Learning

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    Date
    2021
    Author
    Sperrle, Fabian ORCID
    El-Assady, Mennatallah
    Guo, Grace
    Borgo, Rita
    Chau, Duen Horng
    Endert, Alex ORCID
    Keim, Daniel ORCID
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    Abstract
    Visual analytics systems integrate interactive visualizations and machine learning to enable expert users to solve complex analysis tasks. Applications combine techniques from various fields of research and are consequently not trivial to evaluate. The result is a lack of structure and comparability between evaluations. In this survey, we provide a comprehensive overview of evaluations in the field of human-centered machine learning. We particularly focus on human-related factors that influence trust, interpretability, and explainability. We analyze the evaluations presented in papers from top conferences and journals in information visualization and human-computer interaction to provide a systematic review of their setup and findings. From this survey, we distill design dimensions for structured evaluations, identify evaluation gaps, and derive future research opportunities.
    BibTeX
    @article {10.1111:cgf.14329,
    journal = {Computer Graphics Forum},
    title = {{A Survey of Human-Centered Evaluations in Human-Centered Machine Learning}},
    author = {Sperrle, Fabian and El-Assady, Mennatallah and Guo, Grace and Borgo, Rita and Chau, Duen Horng and Endert, Alex and Keim, Daniel},
    year = {2021},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.14329}
    }
    URI
    https://doi.org/10.1111/cgf.14329
    https://diglib.eg.org:443/handle/10.1111/cgf14329
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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA