Grapevine: A Wine Prediction Algorithm Using Multi-dimensional Clustering Methods

TL;DR

Grapevine is a wine recommendation system that uses multidimensional clustering of reviews to suggest wines based on flavor preferences and price-quality optimization.

Contribution

The paper introduces a novel recommendation algorithm combining multidimensional clustering with unsupervised learning for personalized wine suggestions.

Findings

Effective clustering of wine reviews into flavor groups

Improved recommendation accuracy based on user preferences

Optimized wine suggestions balancing price and quality

Abstract

We present a method for a wine recommendation system that employs multidimensional clustering and unsupervised learning methods. Our algorithm first performs clustering on a large corpus of wine reviews. It then uses the resulting wine clusters as an approximation of the most common flavor palates, recommending a user a wine by optimizing over a price-quality ratio within clusters that they demonstrated a preference for.