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ONYX - User Interfaces for Assisting in Interactive Task Learning for Natural Language Interfaces of Data Visualization Tools

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Published:28 April 2022Publication History

ABSTRACT

While natural language interfaces (NLIs) are increasingly utilized to simplify the interaction with data visualization tools, improving and adapting the NLIs to the individual needs of users still requires the support of developers. ONYX introduces an interactive task learning (ITL) based approach which enables NLIs to learn from users through natural interactions. Users can personalize the NLI with new commands using direct manipulation, known commands, or by combining both. To further support users during the training process, we derived two design goals for the user interface, namely providing suggestions based on sub-parts of the command and addressing ambiguities through follow-up questions and instantiated them in ONYX. In order to trigger reflections and gain feedback on possible design trade-offs of ONYX and the instantiated design goals, we performed a formative user study to understand how to successfully integrate the suggestions and follow-up question into the interaction.

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  • Published in

    cover image ACM Conferences
    CHI EA '22: Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems
    April 2022
    3066 pages
    ISBN:9781450391566
    DOI:10.1145/3491101

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