DeepAI AI Chat
Log In Sign Up

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

06/29/2018
by   Richard Diehl Martinez, et al.
Stanford University
0

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.

READ FULL TEXT
12/27/2016

Clustering with Confidence: Finding Clusters with Statistical Guarantees

Clustering is a widely used unsupervised learning method for finding str...
04/13/2016

Joint Unsupervised Learning of Deep Representations and Image Clusters

In this paper, we propose a recurrent framework for Joint Unsupervised L...
08/01/2017

Deriving Verb Predicates By Clustering Verbs with Arguments

Hand-built verb clusters such as the widely used Levin classes (Levin, 1...
10/14/2019

DISCERN: Diversity-based Selection of Centroids for k-Estimation and Rapid Non-stochastic Clustering

As one of the most ubiquitously applied unsupervised learning methods, c...
01/19/2011

Transductive-Inductive Cluster Approximation Via Multivariate Chebyshev Inequality

Approximating adequate number of clusters in multidimensional data is an...
08/20/2014

Introduction to Clustering Algorithms and Applications

Data clustering is the process of identifying natural groupings or clust...
12/23/2021

Ensemble Method for Cluster Number Determination and Algorithm Selection in Unsupervised Learning

Unsupervised learning, and more specifically clustering, suffers from th...