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MovieLens

MovieLens is a recommender system and virtual community website that recommends movies for its users to watch, based on their film preferences using… 
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Cold startCollaborative filteringGroupLens ResearchItem-item collaborative filtering

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
A new recommendation algorithm combined with spectral clustering and transfer learning
Collaborative filtering (CF) recommendation algorithm has been successfully applied into recommender systems for years which can… 
2014
2014
Learning from explanations in recommender systems
2014
2014
From blurry numbers to clear preferences: A mechanism to extract reputation in social networks
2014
2014
Content-Boosted Restricted Boltzmann Machine for Recommendation
Collaborative filtering and Content-based filtering methods are two famous methods used by recommender systems. Restricted Boltz… 
2009
2009
Collaborative Filtering Based on Demographic Attribute Vector
  • Tian ChenLiang He
  • ETP International Conference on Future Computer…
  • 2009
  • Corpus ID: 7824215
In present recommender systems, users receive items recommended on basis of their purchase records. New user experiences the cold… 
2009
2009
An iterative semi-explicit rating method for building collaborative recommender systems
2008
2008
Ant Colony Metaphor Applied in User Interface Recommendation
In this paper web–based system user interface hybrid recommendation method based on the ant colony metaphor is presented. We… 
Review
2006
Review
2006
Deriving ratings through social network structures
A review of existing approaches to recommendation in e-commerce systems is provided. A recommendation system is primarily used to… 
2005
2005
Heterogeneous Attribute Utility Model: A new approach for modeling user profiles for recommendation systems
Reference LIA-CONF-2006-003 URL: http://db.cs.ualberta.ca/webkdd05/ Record created on 2006-05-19, modified on 2017-05-12 
2004
2004
An Accurate and Scalable Collaborative Recommender
We present a collaborative recommender that uses a user-based model to predict user ratings for specified items. The model… 
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