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dc.contributor.authorHaussmann, Steven
dc.contributor.authorChen, Yu
dc.contributor.authorSeneviratne, Oshani
dc.contributor.authorRastogi, Nidhi
dc.contributor.authorCodella, James
dc.contributor.authorChen, Ching Hua
dc.contributor.authorMcGuinness, Deborah
dc.contributor.authorZaki, Mohammed
dc.date.accessioned2022-02-15T17:38:15Z
dc.date.available2022-02-15T17:38:15Z
dc.date.issued2019-10-01
dc.identifier.other26
dc.identifier.urihttp://ceur-ws.org/Vol-2456/paper71.pdf
dc.description.abstractWe demonstrate the usage of our FoodKG [3], a food knowledge graph designed to assist in food recommendation. This resource, which brings together recipes, nutrition, food taxonomies, and links into existing ontologies, is used to power a cognitive agent that performs knowledge-base question answering, primarily to help improve peoples' diets by guiding them towards better foods. The system demonstration involves three categories of questions: simple queries for nutritional information, comparisons of nutrients between dierent foods, and constraintbased queries to nd recipes matching certain criteria.
dc.relation.urihttps://tw.rpi.edu/project/HEALS
dc.subjectHealth Empowerment by Analytics, Learning, and Semantics (HEALS)
dc.titleFoodKG Enabled Questions and Answers Application


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