A Survey on Recommendation Systems using Collaborative Filtering Techniques

Prabakaran, R.; Pradeepkandhasamy, J.; Arun, M.

doi:10.1109/icssit55814.2023.10060889

Cited by 8 publications

(1 citation statement)

References 19 publications

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“…This approach combines a short-term intelligent system with an optimization scenario that considers both tangible and intangible nutritional and personal taste knowledge, as well as nutrient context systems that use an MCDA approach to filter out inappropriate food choices. [11].…”

Section: Literature Surveymentioning

confidence: 99%

Diet Recommendation System Using ML

et al. 2023

Recent Trends in Data Science and Its Applications

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Diabetes interacts with the capacity of our bodies to turn food into energy. It is a chronic health issue. Your pancreas is prompted to generate insulin when the sugar levels in your blood rise since an enormous portion of the food you consume gets transformed into sugar (glucose) and communicated into blood for circulation. Nowadays, deep learning is used in the healthcare industry to try and forecast diseases. Data is the most essential component of deep learning. p A deep learning model is constructed using the previous dataset, which is gathered. Univariate and bivariate analysis, among other essential pre-processing techniques, are used. A classification model is built using a machine learning algorithm only after data is shown to facilitate with feature interpretation. Algorithms are evaluated based on performance metrics like accuracy, F1-score, recall, etc.

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Section: Literature Surveymentioning

confidence: 99%