DOCSLIB.ORG
Explore
Sign Up
Log In
Upload
Search
Home
» Tags
» MovieLens
MovieLens
Evaluation of Recommendation System for Sustainable E-Commerce: Accuracy, Diversity and Customer Satisfaction
Collaborative Filtering: a Machine Learning Perspective by Benjamin Marlin a Thesis Submitted in Conformity with the Requirement
A Recommender System for Groups of Users
Indian Regional Movie Dataset for Recommender Systems
Recommender Systems User-Facing Decision Support Systems
Incorporating Contextual Information in Recommender Systems Using a Multidimensional Approach
Arxiv:1606.07659V3 [Cs.LG] 29 Dec 2017 Rate This Item
Movie Recommendations Using Matrix Factorization
Matrix Factorization Technique for Movielens Recommender System
User- and System Initiated Approaches to Content Discovery
Combining Multiple Metadata Types in Movies Recommendation Using Ensemble Algorithms
Improve the “Long Tail" Recommendation Through Popularity-Sensitive Clustering
Item-Based Collaborative Filtering Recommendation Algorithms
From Head to Long Tail: Efficient and Flexible Recommendation Using Cosine Patterns
An Intelligent System of the Content Relevance at the Example of Films According to User Needs
Learning a Joint Search and Recommendation Model from User-Item Interactions Hamed Zamani∗ W
A Recommendation Engine for Predicting Movie Ratings Using a Big Data Approach
Collaborative Filtering Recommender Systems Contents
Top View
Applying Collaborative Filtering Techniques to Movie Search for Better Ranking and Browsing
Collaborative Filtering Recommender Systems
Collaborative Filtering with User-Item Co-Autoregressive Models
An Item–Item Collaborative Filtering Recommender System Using Trust and Genre to Address the Cold-Start Problem
Metadata in Movies Recommendation: a Comparison Among Different Approaches
Movie Recommender Systems: Implementation and Performace Evaluation
Managing Popularity Bias in Recommender Systems with Personalized Re-Ranking
Which Recommender System Can Best Fit Social Learning Platforms?
Controlling Popularity Bias in Learning to Rank Recommendation
Scalable Realistic Recommendation Datasets Through Fractal Expansions
A Switching Multi-Level Method for the Long Tail Recommendation Problem
For Decision Support Systems Manuscript Draft Manuscript Number
The Unfairness of Popularity Bias in Recommendation∗
A Hybrid Approach to Recommend Long Tail Items
Stability of Collaborative Filtering Recommendation Algorithms1
Enhancing User Experience with Recommender Systems Beyond Prediction Accuracies
A Recommender System Based on Collaborative Filtering Using Ontology and Dimensionality Reduction Techniques
Challenging the Long Tail Recommendation
RECOMMENDATION SYSTEM USING COLLABORATIVE FILTERING Yunkyoung Lee San Jose State University
Content-Based Recommender System for Movie Website
The Grouplens Research Project: About Me … Recommenders History of Recommender Systems the Early Years …
Multidirectional Product Support System for Decision Making in Textile Industry Using Collaborative Filtering Methods A
The Long Tail of Recommender Systems and How to Leverage It
CSE 255 Assignment 1 : Movie Rating Prediction Using the Movielens Dataset
Assessing the Performance of Recommender Systems with Movietweetings and Movielens Datasets
Re-Enrichment Learning: Metadata Saliency for the Evolutive Personalization of a Recommender System
Applying Collaborative Filtering Techniques to the Movie Search For
XXXX the Movielens Datasets: History and Context
Using Fuzzy-Logic in Decision Support System Based on Personal Ratings
Neural Interactive Collaborative Filtering Framework
A Review of Content and Collaborative Filtering Approaches on Movielens