AdvancedPythonProject1

Movie Recommender System

Overview

This project is a Python-based movie recommender system that allows users to:

• Search for movies by title
• Rate movies by ID or name
• Get personalized movie recommendations based on:
  • Genre (top-rated movies in a specific genre)
  • User similarity (movies liked by users with similar taste)

It uses the MovieLens dataset (movies.csv and ratings.csv) and supports interaction through a simple text-based menu.

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Features

1. Search Movies

• Search any movie by title.
• Displays matching results with their average rating.

2. Rate Movies

• Enter a movie ID or part of a movie title to find and rate it.
• If multiple matches exist, the program lists them so you can pick the correct one.
• Your rating updates the movie’s average rating.

3. Get Recommendations

Choose between:

• genre → Lists all available genres and recommends the top-rated movies in that genre.
• user → Finds the most similar user and recommends movies they liked that you haven’t rated yet.
  Each recommendation includes the movie title and average rating.

4. Exit

• Cleanly exits the program.

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How It Works

Data Loading

• MovieDatabase loads data from movies.csv and ratings.csv.
• Builds dictionaries for:
  • movies → {movieId: Movie object}
  • users → {userId: set of movieIds rated}
  • genres → {genre_name: set of movieIds}

Movie Representation

Each movie is stored as a Movie object with:

• id, title, genres, and a list of ratings
• Method average_rating() to calculate its mean rating.

Recommenders

• GenreRecommender:
  Suggests top 5 movies in a given genre based on average ratings.
• UserSimilarityRecommender:
  Finds the most similar user (based on overlapping rated movies) and recommends the top 5 new movies they’ve rated highly.

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How to Run

Requirements

• Python 3.8 or later
• Pandas library

Installation

pip install pandas