Abstract
With the rapid development of the domestic catering industry, people are gradually concerned about the health problems that come with it. Traditional diet recommendation can help users alleviate the information overload problem, but there are problems such as data sparsity and recommendation results are less accurate. The new auxiliary new type of rich entity semantic association contained in the diet knowledge graph can mitigate the disadvantages of cold start; at same time, the related information in the healthy diet graph is applied to the recommendation system through knowledge representation to recommend suitable dishes for users. This paper will research the design and construction of Chinese dietary knowledge graphs from data sources, knowledge graph data acquisition, knowledge graph data fusion, knowledge graph storage five levels to build a complete knowledge map of Chinese healthy eating, laying a solid foundation for subsequent research.
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Acknowledgement
This work is partially supported by the National Natural Science Foundation of China (62162020), the Hainan Province Science and Technology Special Fund (ZDYF2021GXJS216), the Science Project of Hainan University (KYQD(ZR)20021).
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Liu, Z., Su, L., Ye, J., Wang, L. (2023). Construction of Chinese Healthy Eating Knowledge Graph. In: Hung, J.C., Yen, N.Y., Chang, JW. (eds) Frontier Computing. FC 2022. Lecture Notes in Electrical Engineering, vol 1031. Springer, Singapore. https://doi.org/10.1007/978-981-99-1428-9_264
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DOI: https://doi.org/10.1007/978-981-99-1428-9_264
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