Restaurant Recommender

I developed a Knowledge-Based Restaurant Recommendation System that suggests restaurants based on explicit user preferences such as cuisine, location, and budget. Unlike collaborative filtering systems, this approach eliminates the cold-start problem by relying on restaurant attributes instead of past user behavior.

The system was built using Python, Pandas, and Streamlit, and uses real restaurant data from the Zomato dataset to generate personalized recommendations.

Recommendation Engine:

•Filters restaurants based on:

•Cuisine preference

•Location

•Budget level

•Ranks results using a weighted scoring function based on:

•User rating

•Number of votes (credibility)

•Normalizes scores and returns Top-N recommendations

•Provides human-readable explanations for each recommendation