HUMMUS: A Linked, Healthiness-Aware, User-centered and Argument-Enabling Recipe Data Set for Recommendation
Author:
Affiliation:
1. CNRS, UCBL, LIRIS, UMR5205, Univ Lyon, INSA Lyon, France and University of Passau, Germany
2. CNRS, UCBL, LIRIS, UMR5205, Univ Lyon, INSA Lyon, France
3. University of Passau, Germany
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3604915.3609491
Reference71 articles.
1. 2013. SPARQL 1.1 Overview. W3C Recommendation. W3C. https://www.w3.org/TR/2013/REC-sparql11-overview-20130321/. 2013. SPARQL 1.1 Overview. W3C Recommendation. W3C. https://www.w3.org/TR/2013/REC-sparql11-overview-20130321/.
2. 2021. RDF-star and SPARQL-star. Final W3C Community Group Report. W3C Community Group. https://w3c.github.io/rdf-star/cg-spec/2021-12-17.html. 2021. RDF-star and SPARQL-star. Final W3C Community Group Report. W3C Community Group. https://w3c.github.io/rdf-star/cg-spec/2021-12-17.html.
3. Food Standards Agency. 2018. Nutrition labelling. https://www.food.gov.uk/business-guidance/nutrition-labelling Food Standards Agency. 2018. Nutrition labelling. https://www.food.gov.uk/business-guidance/nutrition-labelling
4. Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation
5. 5. Lifestyle Management: Standards of Medical Care in Diabetes—2019;American Diabetes Association;Diabetes Care,2019
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