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Rostami, Ali; Nagesh, Nitish; Rahmani, Amir; Jain, Ramesh
World Food Atlas for Food Navigation Conference
MADiMa '22: Proceedings of the 7th International Workshop on Multimedia Assisted Dietary Management, 2022.
Abstract | Links | BibTeX | Tags: Food Knowledge Graph, Food Recommendation, Food Schema, Health Effect Queries, Health Navigation, Personal Food Model, Recipe Dataset
@conference{nokey,
title = {World Food Atlas for Food Navigation},
author = {Ali Rostami and Nitish Nagesh and Amir Rahmani and Ramesh Jain},
url = {https://dl.acm.org/doi/10.1145/3552484.3555748},
doi = {10.1145/3552484.3555748},
year = {2022},
date = {2022-10-01},
urldate = {2022-10-01},
booktitle = {MADiMa '22: Proceedings of the 7th International Workshop on Multimedia Assisted Dietary Management},
pages = {39–47},
abstract = {Food plays a central role in agriculture, public wellness, public health, culinary art, and culture. Food-related data is available in varying formats and with different access levels ranging from private datasets to publicly downloadable data. Every food-related query, in principle, is a food recommendation problem. We analyze the components of a food recommendation and its requirements. We demonstrate the effectiveness of having access to worldwide food data from divergent aspects for answering food- and health-related queries that would otherwise be expensive and require specialized domain expertise. We present the World Food Atlas (WFA): An open-source platform for different stakeholders in the food ecosystem to share their data on a global data hub with a singular point of access. The world food atlas contains the availability and interconnectivity of food and its effects in various forms. We gather real-world questions by partnering with nutritionists, dietitians, and doctors. We categorize the practical food queries to construct requirement tables and develop a novel schema to satisfy the requirement table to model the world food atlas. Finally, we demonstrate how food and lifestyle navigation systems can use the world food atlas to enable personalized and context-driven solutions to person-entity-context queries.},
keywords = {Food Knowledge Graph, Food Recommendation, Food Schema, Health Effect Queries, Health Navigation, Personal Food Model, Recipe Dataset},
pubstate = {published},
tppubtype = {conference}
}
Food plays a central role in agriculture, public wellness, public health, culinary art, and culture. Food-related data is available in varying formats and with different access levels ranging from private datasets to publicly downloadable data. Every food-related query, in principle, is a food recommendation problem. We analyze the components of a food recommendation and its requirements. We demonstrate the effectiveness of having access to worldwide food data from divergent aspects for answering food- and health-related queries that would otherwise be expensive and require specialized domain expertise. We present the World Food Atlas (WFA): An open-source platform for different stakeholders in the food ecosystem to share their data on a global data hub with a singular point of access. The world food atlas contains the availability and interconnectivity of food and its effects in various forms. We gather real-world questions by partnering with nutritionists, dietitians, and doctors. We categorize the practical food queries to construct requirement tables and develop a novel schema to satisfy the requirement table to model the world food atlas. Finally, we demonstrate how food and lifestyle navigation systems can use the world food atlas to enable personalized and context-driven solutions to person-entity-context queries.
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