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[PDF] Food Recommendation System Project Report | Semantic Scholar
Sign in. Being nutrition one of the biggest modifiable factors in our lives, small changes can have a big impact. With the exponential increase in the number of available food options, it is not possible to take them all into account anymore. The only way to consider user preferences, maximize the number of healthy compounds and minimize the unhealthy ones in food, is using 3D recommendation systems. Train, evaluate and test a model able to predict cuisines from sets of ingredients. Estimate the probability of negative recipe-drug interactions based on the predicted cuisine.
This paper explores the role of the global food system as the principal driver of accelerating biodiversity loss. It explains how food production is degrading or destroying natural habitats and contributing to species extinction. The first is to change dietary patterns to reduce food demand and encourage more plant-based diets. The second is to protect and set aside land for nature, whether through re-establishing native ecosystems on spared farmland or integrating pockets of natural habitat into farmland.
The challenge was not just to provide researchers with very rich publications at any time, any place and in any form but to also offer the right publication to the right researcher in the right way. Several approaches exist in handling paper recommender systems. However, these approaches assumed the availability of the whole contents of the recommending papers to be freely accessible, which is not always true due to factors such as copyright restrictions.