COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Selective Sampling Using the Query by Committee Algorithm
Machine Learning
A re-examination of text categorization methods
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Latent Class Models for Collaborative Filtering
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Employing EM and Pool-Based Active Learning for Text Classification
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Collaborative filtering via gaussian probabilistic latent semantic analysis
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Support vector machine active learning with applications to text classification
The Journal of Machine Learning Research
A Bayesian approach toward active learning for collaborative filtering
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Document classification through interactive supervision of document and term labels
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Google news personalization: scalable online collaborative filtering
Proceedings of the 16th international conference on World Wide Web
Towards design principles for effective context- and perspective-based web mining
Proceedings of the 4th International Conference on Design Science Research in Information Systems and Technology
Personalized music emotion recognition
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Probabilistic latent semantic user segmentation for behavioral targeted advertising
Proceedings of the Third International Workshop on Data Mining and Audience Intelligence for Advertising
A brief survey of computational approaches in social computing
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Active learning driven by rating impact analysis
Proceedings of the fourth ACM conference on Recommender systems
CiteData: a new multi-faceted dataset for evaluating personalized search performance
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Music recommendation by unified hypergraph: combining social media information and music content
Proceedings of the international conference on Multimedia
Functional matrix factorizations for cold-start recommendation
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
Collaborative filtering with collective training
Proceedings of the fifth ACM conference on Recommender systems
Batch Mode Active Learning for Networked Data
ACM Transactions on Intelligent Systems and Technology (TIST)
Dynamically generating context-relevant sub-webs
DESRIST'10 Proceedings of the 5th international conference on Global Perspectives on Design Science Research
Using control theory for stable and efficient recommender systems
Proceedings of the 21st international conference on World Wide Web
Adaptive diversification of recommendation results via latent factor portfolio
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Exploiting the characteristics of matrix factorization for active learning in recommender systems
Proceedings of the sixth ACM conference on Recommender systems
Efficiently learning the preferences of people
Machine Learning
Learning multiple-question decision trees for cold-start recommendation
Proceedings of the sixth ACM international conference on Web search and data mining
Interactive collaborative filtering
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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
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Collaborative Filtering (CF) requires user-rated training examples for statistical inference about the preferences of new users. Active learning strategies identify the most informative set of training examples through minimum interactions with the users. Current active learning approaches in CF make an implicit and unrealistic assumption that a user can provide rating for any queried item. This paper introduces a new approach to the problem which does not make such an assumption. We personalize active learning for the user, and query for only those items which the user can provide rating for. We propose an extended form of Bayesian active learning and use the Aspect Model for CF to illustrate and examine the idea. A comparative evaluation of the new method and a well-established baseline method on benchmark datasets shows statistically significant improvements with our method over the performance of the baseline method that is representative for existing approaches which do not take personalization into account.