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Netflix Prize
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The Netflix Prize Contest
Lessons Learned from the Netflix Contest Arthur Dunbar
Netflix and the Development of the Internet Television Network
Introduction
ŠKODA AUTO VYSOKÁ ŠKOLA O.P.S. Valuation of Netflix, Inc. Diploma
When Diversity Met Accuracy: a Story of Recommender Systems †
Binary Principal Component Analysis in the Netflix Collaborative Filtering Task
UNIVERSITY of CALIFORNIA, SAN DIEGO Bag-Of-Concepts As a Movie
Statistical Significance of the Netflix Challenge
Movie Recommendations Using Matrix Factorization
Ensemble Learning Featuring the Netflix Prize Competition And
Statistical Learning, Fall 2014-15 Class Competition: Netflix Data
Signature Redactedn '- Patrick Hale, Director System Design and Management Program Abstract
Matrix Factorization Technique for Movielens Recommender System
Interview with Simon Funk Gregory Piatetsky Kdnuggets Editor at Kdnuggets
Netflix: the Streaming Challenge1
Variational Autoencoders for Collaborative Filtering
Top View
An Intelligent System of the Content Relevance at the Example of Films According to User Needs
A Preliminary Study on a Recommender System for the Million Songs Dataset Challenge
Netflix Movie Rating Analysis
The Netflix Prize
Lecture 15: CS 5306 / INFO 5306: Crowdsourcing and Human Computation
Mining Large Streams of User Data for Personalized Recommendations
A Study on User Demographic Inference Via Ratings In
Big & Personal: Data and Models Behind Netflix Recommendations
Matrix Factorization Techniques for Recommender Systems
2.1 Goals of the Session 2.2 Netflix
Algorithms and the Streaming Wars: the Changing Meanings of Film
The-Netflix-Prize-Bennett.Pdf
Behavioral Changes of the Audience by the Algorithmic Recommendation Systems Inside Video-On-Demand
Lessons from the Netflix Prize: Going Beyond the Algorithms Yehuda Koren
The Bellkor 2008 Solution to the Netflix Prize
Lecture 8 Web Mining and Recommender Systems
Movrec: a Personalized Movie Recommendation System for Children Based on Online Movie Features∗
Statistical Learning, Fall 2007/08
The Netflix Prize and Production Machine Learning Systems: an Insider Look
Spotify's Collaborative Filtering
Lessons from the Netflix Prize
Large-Scale Recommender Systems and the Netflix Prize Competition
Fast Greedy MAP Inference for Determinantal Point Process to Improve Recommendation Diversity
Université De Montréal REPRESENTATION LEARNING
Recommend a Movie, Win a Million Bucks
Review Article a Survey of Collaborative Filtering Techniques
2013 Netflix Strategic Analysis
Matrix Completion and Large-Scale SVD Computations
The Netflix Prize and Production Machine Learning Systems: an Insider Look Posted by Loren Shure, April 22, 2015
Metadata-Based Collaborative Filtering Using K-Partite Graph for Movie Recommendation
The Netflix Prize Rules
UC San Diego Electronic Theses and Dissertations
Distributed Matrix Factorization with Mapreduce Using a Series of Broadcast-Joins
The Netflix Experience: a User-Focused Approach to the Netflix Recommendation Algorithm In: Theo Plothe, Amber M