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'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake
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An Interactive Knowledge and Learning Environment in Smart Foodsheds.

Yamei Tu, Xiaoqi Wang, Rui Qiu

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    |April 8, 2023
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    Summary
    This summary is machine-generated.

    The Internet of Food (IoF) knowledge graph is complex. An interactive knowledge and learning environment (IKLE) simplifies data analysis for smart foodsheds using automated language generation and visualization.

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    Area of Science:

    • Computer Science
    • Agricultural Science
    • Food Science

    Background:

    • The Internet of Food (IoF) is an emerging field creating large, heterogeneous knowledge graphs (KGs) for smart foodsheds.
    • Challenges exist in information retrieval and interactive exploration due to KG complexity.

    Purpose of the Study:

    • To develop an interactive knowledge and learning environment (IKLE) to address challenges in IoF KG analysis.
    • To support multiple downstream tasks within the IoF analysis pipeline.

    Main Methods:

    • Integrated three programming and modeling languages within IKLE.
    • Developed algorithms for automated language generation.
    • Designed a dataflow visualization system for pipeline construction.

    Main Results:

    • IKLE facilitates easier use of complex IoF data.
    • Automated language generation simplifies the analysis process.
    • The dataflow visualization system enables intuitive pipeline building.

    Conclusions:

    • IKLE effectively addresses the challenges of analyzing large, heterogeneous IoF knowledge graphs.
    • The system enhances user interaction and downstream task performance in smart foodsheds.
    • Demonstrated effectiveness through three real-world case studies.