Movie-genre-prediction

Objective

The goal of this competition is to design a predictive model that accurately classifies movies into their respective genres based on their titles and synopses.

The challenge lies not just in achieving high accuracy, but also in ensuring that the model is efficient and interpretable.

Why This is Interesting and Relevant

Understanding movie genres based on titles and synopses is a fascinating problem for multiple reasons.

From a recommendation system perspective, an effective genre classifier can help build more personalized user recommendations, increasing user engagement on streaming platforms.

In the context of box office performance, understanding the relationship between genres and how they are perceived in synopses can provide insight into patterns of commercial success or failure.

Furthermore, this challenge can facilitate a deeper comprehension of movie themes and trends in the industry, contributing to cultural and societal studies.

Dataset

Participants will be provided with a comprehensive dataset comprising ~100,000 movies. Each entry includes the original title, the genre(s), and the synopsis of the movie.

The dataset contains a mix of both original and AI-generated titles, genres, and synopses to test the robustness of the models.

The 10 genres include action, adventure, crime, family, fantasy, horror, mystery, romance, scifi, and thriller.