GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Proceedings of the 11th international conference on World Wide Web
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
Eigentaste: A Constant Time Collaborative Filtering Algorithm
Information Retrieval
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
Collaborative Filtering by Personality Diagnosis: A Hybrid Memory and Model-Based Approach
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
An Efficient Boosting Algorithm for Combining Preferences
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Scaling personalized web search
WWW '03 Proceedings of the 12th international conference on World Wide Web
Collaborative filtering with decoupled models for preferences and ratings
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Latent semantic models for collaborative filtering
ACM Transactions on Information Systems (TOIS)
ACM Transactions on Internet Technology (TOIT)
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
Effective missing data prediction for collaborative filtering
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Journal of Artificial Intelligence Research
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Proceedings of the Second ACM International Conference on Web Search and Data Mining
CARES: a ranking-oriented CADAL recommender system
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
Grocery shopping recommendations based on basket-sensitive random walk
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning to recommend with social trust ensemble
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Ordering innovators and laggards for product categorization and recommendation
Proceedings of the third ACM conference on Recommender systems
Learning to recommend with trust and distrust relationships
Proceedings of the third ACM conference on Recommender systems
Probabilistic latent preference analysis for collaborative filtering
Proceedings of the 18th ACM conference on Information and knowledge management
Proceedings of the 18th ACM conference on Information and knowledge management
A brief survey of computational approaches in social computing
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Separating the reputation and the sociability of online community users
Proceedings of the 2010 ACM Symposium on Applied Computing
Temporal recommendation on graphs via long- and short-term preference fusion
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
The task-dependent effect of tags and ratings on social media access
ACM Transactions on Information Systems (TOIS)
Aggregating preference graphs for collaborative rating prediction
Proceedings of the fourth ACM conference on Recommender systems
Optimizing multiple objectives in collaborative filtering
Proceedings of the fourth ACM conference on Recommender systems
List-wise learning to rank with matrix factorization for collaborative filtering
Proceedings of the fourth ACM conference on Recommender systems
Adapting neighborhood and matrix factorization models for context aware recommendation
Proceedings of the Workshop on Context-Aware Movie Recommendation
FactRank: random walks on a web of facts
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Music recommendation by unified hypergraph: combining social media information and music content
Proceedings of the international conference on Multimedia
Recommender systems with social regularization
Proceedings of the fourth ACM international conference on Web search and data mining
CMAP: effective fusion of quality and relevance for multi-criteria recommendation
Proceedings of the fourth ACM international conference on Web search and data mining
Categorising social tags to improve folksonomy-based recommendations
Web Semantics: Science, Services and Agents on the World Wide Web
Learning to recommend with explicit and implicit social relations
ACM Transactions on Intelligent Systems and Technology (TIST)
A social network-aware top-N recommender system using GPU
Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
Probabilistic factor models for web site recommendation
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
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
Using rich social media information for music recommendation via hypergraph model
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) - Special section on ACM multimedia 2010 best paper candidates, and issue on social media
Informative household recommendation with feature-based matrix factorization
Proceedings of the 2nd Challenge on Context-Aware Movie Recommendation
Goal-driven collaborative filtering – a directional error based approach
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Factorization Machines with libFM
ACM Transactions on Intelligent Systems and Technology (TIST)
Impact and degree of user sociability in social media
Information Sciences: an International Journal
Recommend at opportune moments
AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
Feature based informative model for discriminating favorite items from unrated ones
APWeb'12 Proceedings of the 14th Asia-Pacific international conference on Web Technologies and Applications
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
Collaborative personalized tweet recommendation
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Dual role model for question recommendation in community question answering
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Local implicit feedback mining for music recommendation
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
Adapting vector space model to ranking-based collaborative filtering
Proceedings of the 21st ACM international conference on Information and knowledge management
Learning to rank for hybrid recommendation
Proceedings of the 21st ACM international conference on Information and knowledge management
Importance weighted passive learning
Proceedings of the 21st ACM international conference on Information and knowledge management
Top-N recommendation through belief propagation
Proceedings of the 21st ACM international conference on Information and knowledge management
A modified random walk framework for handling negative ratings and generating explanations
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context
Social temporal collaborative ranking for context aware movie recommendation
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context
Mining contextual movie similarity with matrix factorization for context-aware recommendation
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context
Unifying rating-oriented and ranking-oriented collaborative filtering for improved recommendation
Information Sciences: an International Journal
Serendipitous Personalized Ranking for Top-N Recommendation
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Nontrivial landmark recommendation using geotagged photos
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Sections on Paraphrasing; Intelligent Systems for Socially Aware Computing; Social Computing, Behavioral-Cultural Modeling, and Prediction
An experimental study on implicit social recommendation
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Optimizing top-n collaborative filtering via dynamic negative item sampling
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
GAPfm: optimal top-n recommendations for graded relevance domains
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Interactive collaborative filtering
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Diffusion-aware personalized social update recommendation
Proceedings of the 7th ACM conference on Recommender systems
Collaborative pseudo-relevance feedback
Expert Systems with Applications: An International Journal
Type Extension Trees for feature construction and learning in relational domains
Artificial Intelligence
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
Modeling and broadening temporal user interest in personalized news recommendation
Expert Systems with Applications: An International Journal
Proceedings of the 23rd international conference on World wide web
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A recommender system must be able to suggest items that are likely to be preferred by the user. In most systems, the degree of preference is represented by a rating score. Given a database of users' past ratings on a set of items, traditional collaborative filtering algorithms are based on predicting the potential ratings that a user would assign to the unrated items so that they can be ranked by the predicted ratings to produce a list of recommended items. In this paper, we propose a collaborative filtering approach that addresses the item ranking problem directly by modeling user preferences derived from the ratings. We measure the similarity between users based on the correlation between their rankings of the items rather than the rating values and propose new collaborative filtering algorithms for ranking items based on the preferences of similar users. Experimental results on real world movie rating data sets show that the proposed approach outperforms traditional collaborative filtering algorithms significantly on the NDCG measure for evaluating ranked results.