research-article

MI3: Machine-initiated Intelligent Interaction for Interactive Classification and Data Reconstruction

Authors:

Min ChenAuthors Info & Claims

ACM Transactions on Interactive Intelligent Systems (TiiS), Volume 11, Issue 3-4

Article No.: 18, Pages 1 - 34

https://doi.org/10.1145/3412848

Published: 03 September 2021 Publication History

Abstract

In many applications, while machine learning (ML) can be used to derive algorithmic models to aid decision processes, it is often difficult to learn a precise model when the number of similar data points is limited. One example of such applications is data reconstruction from historical visualizations, many of which encode precious data, but their numerical records are lost. On the one hand, there is not enough similar data for training an ML model. On the other hand, manual reconstruction of the data is both tedious and arduous. Hence, a desirable approach is to train an ML model dynamically using interactive classification, and hopefully, after some training, the model can complete the data reconstruction tasks with less human interference. For this approach to be effective, the number of annotated data objects used for training the ML model should be as small as possible, while the number of data objects to be reconstructed automatically should be as large as possible. In this article, we present a novel technique for the machine to initiate intelligent interactions to reduce the user’s interaction cost in interactive classification tasks. The technique of machine-initiated intelligent interaction (MI3) builds on a generic framework featuring active sampling and default labeling. To demonstrate the MI3 approach, we use the well-known cholera map visualization by John Snow as an example, as it features three instances of MI3 pipelines. The experiment has confirmed the merits of the MI3 approach.

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Cited By

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https://dl.acm.org/doi/10.1145/3640543.3645145
Zhang YTennekes MDe Jong TCurier LCoecke BChen M(2024)Simulation-based Optimization of User Interfaces for Quality-assuring Machine Learning Model PredictionsACM Transactions on Interactive Intelligent Systems10.1145/359455214:1(1-32)Online publication date: 9-Jan-2024
https://dl.acm.org/doi/10.1145/3594552
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https://doi.org/10.11834/jig.230034
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Index Terms

MI3: Machine-initiated Intelligent Interaction for Interactive Classification and Data Reconstruction

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cover image ACM Transactions on Interactive Intelligent Systems

ACM Transactions on Interactive Intelligent Systems Volume 11, Issue 3-4

December 2021

483 pages

ISSN:2160-6455

EISSN:2160-6463

DOI:10.1145/3481699

Editor:
Michelle X. Zhou
Juji, Inc., USA

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Publication History

Published: 03 September 2021

Accepted: 01 July 2021

Revised: 01 June 2020

Received: 01 November 2019

Published in TIIS Volume 11, Issue 3-4

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Cited By

Lyu HBai YLiang XDas UShi CGong LLi YSun MGe MMa X(2024)FARPLS: A Feature-Augmented Robot Trajectory Preference Labeling System to Assist Human Labelers’ Preference ElicitationProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645145(344-369)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645145
Zhang YTennekes MDe Jong TCurier LCoecke BChen M(2024)Simulation-based Optimization of User Interfaces for Quality-assuring Machine Learning Model PredictionsACM Transactions on Interactive Intelligent Systems10.1145/359455214:1(1-32)Online publication date: 9-Jan-2024
https://dl.acm.org/doi/10.1145/3594552
Jun TYu ZQing CCan LSiming CXiaoru Y(2023)Intelligent visualization and visual analyticsJournal of Image and Graphics10.11834/jig.23003428:6(1909-1926)Online publication date: 2023
https://doi.org/10.11834/jig.230034
Zhang YJiang RXie LZhao YLiu CDing TChen SYuan X(2023)OldVisOnline: Curating a Dataset of Historical VisualizationsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.332690830:1(551-561)Online publication date: 24-Oct-2023
https://dl.acm.org/doi/10.1109/TVCG.2023.3326908
Zhang YWang YZhang HZhu BChen SZhang D(2022)OneLabeler: A Flexible System for Building Data Labeling ToolsProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3517612(1-22)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3517612
Wang YZhang YShen LWang S(2021)Analysis and Research on Human Movement in Sports SceneComputational Intelligence and Neuroscience10.1155/2021/23766012021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/2376601

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