Recipes Recommender System

dc.contributor.author	Nana, Mais
dc.contributor.author	Musleh, Amal
dc.contributor.author	zraiq, Hala
dc.date.accessioned	2022-11-02T13:22:17Z
dc.date.available	2022-11-02T13:22:17Z
dc.date.issued	2022
dc.description.abstract	Recommendation systems are tools for interacting with large and complex information spaces, they provide a personalized view of these spaces, giving priority to the elements that are likely to be of interest to the user. Most of the big players in the industry like Google, Amazon, EBay, etc. use some sort of recommendation system in the background to recommend personalized products, ads, and videos. Recommendation systems play an important role in helping people find recipes that interest them and match their eating habits, and recommendation systems make use of user profiles, user browsing history, search history, and filtering technologies to gather information and help users find the right information from a large volume of data. The system is a mobile application that works on Android and iOS built using the filter and is used by all ages easily. To build this application, the content-based systems algorithm was used. Goals and Objectives ● Find recipes similar to the user's taste. ● Facilitate the process of preparing and finding meals for users ● Give a satisfactory outcome from the research process	en_US
dc.identifier.uri	https://hdl.handle.net/20.500.11888/18119
dc.language.iso	en	en_US
dc.title	Recipes Recommender System	en_US
dc.type	Graduation project	en_US

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