Ahmed AsifFA16-BCS-459LHR TP 62122026-02-192020-11-20https://repository.cuilahore.edu.pk/handle/123456789/1958In everyday life, people make different decisions but what they need is the saving of time without taking so much time in choosing interested items. Like we can say “Which cities in the country should I visit?”, “Which kind of movies should I see?”, and “What kind of foods should I eat?” and etc. So, to achieve them all we need to have a better system to make quick and better decision on the basis of user interest in very less time or we can say the information should be available all the time. Recommender system helps people make decisions in these complex information spaces. Recommender system do the filtering of information of different items like movies and foods and then recommend or suggest the suitable item to the user according to their interest. Some famous recommender systems which works in the world right now are: Amazon, Ulike and etc. The Recommender system actually gathers or acquires the desired information or interest of the user from her/his social profile. Then by the help of some reference characteristics and predict the rating of an item which would be given by the user. The Recommender system looks for the similarity of foods and movies and for accomplishing this task the system sues the content-based recommendation technique. Basically, my system constructs user profiles from the previously rated features, food and movie profiles from the ingredients of the food and movie, then it recommends the most appropriate foods and movies according to the preferences of the users. In this Recommender System the user can do multiple tasks such as user can create account, add post, comment, user can give rating to post and can send message to admin.Recommender SystemComputer scienceSP16Thesis