Evaluation of the Usage of Graph Database in a Nutrition App for Determining Potential Nutrient Inhibition

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Abstract In recent years, the popularity of veganism has surged, prompting a growing interest in its health implications. While vegan diets offer numerous benefits, they also pose challenges due to potential deficiencies in essential nutrients and the presence of anti-nutrients in plant-based foods. This paper addresses the need for a comprehensive understanding of nutrient interactions, particularly those involving antinutrients, by creating a Knowledge Graph. Utilizing Natural Language Processing techniques, essential nutritional entities were extracted from unstructured texts, and a custom Named Entity Recognition model was implemented. These data were then used to construct a Knowledge Graph using Neo4j, a leading graph database. Despite the potential of the developed Knowledge Graph to visualize nutrient interactions, limitations persist due to the scarcity of available data on antinutrient interactions. Nonetheless, the Knowledge Graph provides a promising avenue for exploring and understanding the complexities of nutrient interactions, facilitating future research and informing dietary choices.

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