RESTAURANT RECOMMENDATION USING AI

Choosing a suitable restaurant can be difficult when users must compare cuisine, price, distance, ratings, dietary needs,and personal preferences across multiple sources. This paper presents a conceptual AI-based Restaurant RecommendationSystem that aims to make restaurant discovery more relevant and efficient. The proposed system collects user preferencessuch as preferred cuisine, budget, location, rating threshold, and dietary requirements. It then filters candidate restaurantsand ranks them using a recommendation score that may combine preference similarity, distance, rating, and affordability.A modular design separates the user interface, data processing, restaurant dataset, recommendation engine, and resultsdisplay. The approach can be implemented using a web or mobile interface and a structured restaurant database. Thesystem is intended to provide personalized suggestions while allowing users to understand why a restaurant wasrecommended. This document is a student research-paper sample; implementation details, dataset sources, measuredresults, and references should be verified and updated according to the student's actual work before submission.