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Related Experiment Video

Updated: Aug 3, 2025

'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake

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Published on: September 18, 2018

An Interactive Knowledge and Learning Environment in Smart Foodsheds.

Yamei Tu, Xiaoqi Wang, Rui Qiu

IEEE Computer Graphics and Applications

|April 8, 2023

Summary

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.