Recipe Recommendation System Using NLP, Deep Learning
Ashmitha B M1, Aleena Tom2, Amal Mathew Paul3 , Abhiroop M P4 ,Aswathy T S5
1DEPT OF CSE(ARTIFICIAL INTELLIGENCE AND DATA SCIENCE)& VIMAL JYOTHI ENGINEERING COLLEGE,CHEMPERI,KANNUR,KERALA
2DEPT OF CSE(ARTIFICIAL INTELLIGENCE AND DATA SCIENCE)& VIMAL JYOTHI ENGINEERING COLLEGE,CHEMPERI,KANNUR,KERALA
3DEPT OF CSE(ARTIFICIAL INTELLIGENCE AND DATA SCIENCE)& VIMAL JYOTHI ENGINEERING COLLEGE,CHEMPERI,KANNUR,KERALA
4DEPT OF CSE(ARTIFICIAL INTELLIGENCE AND DATA SCIENCE)& VIMAL JYOTHI ENGINEERING COLLEGE,CHEMPERI,KANNUR,KERALA
5DEPT OF CSE(ARTIFICIAL INTELLIGENCE AND DATA SCIENCE)& VIMAL JYOTHI ENGINEERING COLLEGE,CHEMPERI,KANNUR,KERALA
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Abstract - In the field of culinary the food and recommendation have a significant role and development. In modern year the use of large-scale datasets, Machine learning techniques and also the personalized health and nutrition were growing prioritized day by day. Literature review includes four various research papers consisting the aspects of recipe recommendation system in an innovative way, that containing user preference elicitation [1],personalized meal planning [3], image to recipe generation [4], and recipe representation learning [2].These papers make highlight of the importance of user focused design, large data combinations, and adaptable in every users and enhance accuracy also the accessibility of food recommendation system. With the use of developed machine learning models, such as collaborative filtering [3],vision transformers [4] and graph neural networks [2].In these mechanism it provides custom solutions for healthy habitual eating and improve the user pleasure. Upcoming research technology includes the IoT methods and adjusting techniques to multiple culture and religious dietary plans. Here introducing the possibility of culinary methods to maintain the dietary plan and being well.
Key Words: Image to recipe generation, recipe representation learning, collaborative filtering, graph neural networks
