Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Learning and Revising User Profiles: The Identification ofInteresting Web Sites
Machine Learning - Special issue on multistrategy learning
Recommendation as classification: using social and content-based information in recommendation
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Effective personalization based on association rule discovery from web usage data
Proceedings of the 3rd international workshop on Web information and data management
Eigentaste: A Constant Time Collaborative Filtering Algorithm
Information Retrieval
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
An efficient boosting algorithm for combining preferences
The Journal of Machine Learning Research
Proceedings of the 10th international conference on Intelligent user interfaces
IEEE Transactions on Knowledge and Data Engineering
Scaling to very very large corpora for natural language disambiguation
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Scalable collaborative filtering using cluster-based smoothing
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Learning to rank using gradient descent
ICML '05 Proceedings of the 22nd international conference on Machine learning
Context-Aware SVM for Context-Dependent Information Recommendation
MDM '06 Proceedings of the 7th International Conference on Mobile Data Management
Learning to rank: from pairwise approach to listwise approach
Proceedings of the 24th international conference on Machine learning
Restricted Boltzmann machines for collaborative filtering
Proceedings of the 24th international conference on Machine learning
AdaRank: a boosting algorithm for information retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Lessons from the Netflix prize challenge
ACM SIGKDD Explorations Newsletter - Special issue on visual analytics
Trust-based recommendation systems: an axiomatic approach
Proceedings of the 17th international conference on World Wide Web
Listwise approach to learning to rank: theory and algorithm
Proceedings of the 25th international conference on Machine learning
Directly optimizing evaluation measures in learning to rank
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Learning classifiers from only positive and unlabeled data
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Factorization meets the neighborhood: a multifaceted collaborative filtering model
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
How does clickthrough data reflect retrieval quality?
Proceedings of the 17th ACM conference on Information and knowledge management
SoRec: social recommendation using probabilistic matrix factorization
Proceedings of the 17th ACM conference on Information and knowledge management
Collaborative Filtering for Implicit Feedback Datasets
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
IEICE - Transactions on Information and Systems
The Unreasonable Effectiveness of Data
IEEE Intelligent Systems
Matchbox: large scale online bayesian recommendations
Proceedings of the 18th international conference on World wide web
TrustWalker: a random walk model for combining trust-based and item-based recommendation
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Collaborative filtering with temporal dynamics
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
The wisdom of the few: a collaborative filtering approach based on expert opinions from the web
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
I Like It... I Like It Not: Evaluating User Ratings Noise in Recommender Systems
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Recommending new movies: even a few ratings are more valuable than metadata
Proceedings of the third ACM conference on Recommender systems
Experimental comparison of pre- vs. post-filtering approaches in context-aware recommender systems
Proceedings of the third ACM conference on Recommender systems
AIMED: a personalized TV recommendation system
EuroITV'07 Proceedings of the 5th European conference on Interactive TV: a shared experience
Content-based recommendation systems
The adaptive web
Hybrid web recommender systems
The adaptive web
Factorizing personalized Markov chains for next-basket recommendation
Proceedings of the 19th international conference on World wide web
BPR: Bayesian personalized ranking from implicit feedback
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Efficient algorithms for ranking with SVMs
Information Retrieval
Training and testing of recommender systems on data missing not at random
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the fourth ACM conference on Recommender systems
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
A stochastic learning-to-rank algorithm and its application to contextual advertising
Proceedings of the 20th international conference on World wide web
Collaborative competitive filtering: learning recommender using context of user choice
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Fast context-aware recommendations with factorization machines
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
Wisdom of the better few: cold start recommendation via representative based rating elicitation
Proceedings of the fifth ACM conference on Recommender systems
The effect of context-aware recommendations on customer purchasing behavior and trust
Proceedings of the fifth ACM conference on Recommender systems
OrdRec: an ordinal model for predicting personalized item rating distributions
Proceedings of the fifth ACM conference on Recommender systems
Power to the people: exploring neighbourhood formations in social recommender system
Proceedings of the fifth ACM conference on Recommender systems
New objective functions for social collaborative filtering
Proceedings of the 21st international conference on World Wide Web
Sparse linear methods with side information for Top-N recommendations
Proceedings of the 21st international conference companion on World Wide Web
TFMAP: optimizing MAP for top-n context-aware recommendation
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Spotting trends: the wisdom of the few
Proceedings of the sixth ACM conference on Recommender systems
On top-k recommendation using social networks
Proceedings of the sixth ACM conference on Recommender systems
Alternating least squares for personalized ranking
Proceedings of the sixth ACM conference on Recommender systems
CLiMF: learning to maximize reciprocal rank with collaborative less-is-more filtering
Proceedings of the sixth ACM conference on Recommender systems
Swarming to rank for recommender systems
Proceedings of the sixth ACM conference on Recommender systems
Big & personal: data and models behind netflix recommendations
Proceedings of the 2nd International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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The Netflix Prize put the spotlight on the use of data mining and machine learning methods for predicting user preferences. Many lessons came out of the competition. But since then, Recommender Systems have evolved. This evolution has been driven by the greater availability of different kinds of user data in industry and the interest that the area has drawn among the research community. The goal of this paper is to give an up-to-date overview of the use of data mining approaches for personalization and recommendation. Using Netflix personalization as a motivating use case, I will describe the use of different kinds of data and machine learning techniques. After introducing the traditional approaches to recommendation, I highlight some of the main lessons learned from the Netflix Prize. I then describe the use of recommendation and personalization techniques at Netflix. Finally, I pinpoint the most promising current research avenues and unsolved problems that deserve attention in this domain.