What you see is what you can change: Human-centered machine learning by interactive visualization

NEUROCOMPUTING

卷:268

Article

Sacha, Dominik¹  Sedlmair, Michael³  Zhang, Leishi⁴  Lee, John A.⁵  Peltonen, Jaakko^6,7  Weiskopf, Daniel⁸  North, Stephen C.⁹  Keim, Daniel A.² 

[1] Univ Konstanz, D-78457 Constance, Germany

[2] Univ Konstanz, Data Anal & Visualizat Res Grp, Comp Sci Dept, D-78457 Constance, Germany

[3] Univ Vienna, A-1090 Vienna, Austria

[4] Middlesex Univ, Data Intens Syst, London NW4 4BT, England

[5] Catholic Univ Louvain, B-1348 Louvain La Neuve, Belgium

[6] Aalto Univ, FI-00076 Aalto, Finland

[7] Univ Tampere, Tampere 33014, Finland

[8] Univ Stuttgart, D-70174 Stuttgart, Germany

[9] Infovisible, Oldwick, NJ 08858 USA

关键词: Machine learning;    Information visualization;    Interaction;    Visual analytics;   

DOI  :  10.1016/j.neucom.2017.01.105

来源: Elsevier

【 摘 要 】

Visual analytics (VA) systems help data analysts solve complex problems interactively, by integrating automated data analysis and mining, such as machine learning (ML) based methods, with interactive visualizations. We propose a conceptual framework that models human interactions with ML components in the VA process, and that puts the central relationship between automated algorithms and interactive visualizations into sharp focus. The framework is illustrated with several examples and we further elaborate on the interactive ML process by identifying key scenarios where ML methods are combined with human feedback through interactive visualization. We derive five open research challenges at the intersection of ML and visualization research, whose solution should lead to more effective data analysis. (C) 2017 Elsevier B.V. All rights reserved.

【 授权许可】

Free