GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Query by humming: musical information retrieval in an audio database
Proceedings of the third ACM international conference on Multimedia
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Fab: content-based, collaborative recommendation
Communications of the ACM
Collecting user access patterns for building user profiles and collaborative filtering
IUI '99 Proceedings of the 4th international conference on Intelligent user interfaces
Jester 2.0 (poster abstract): evaluation of an new linear time collaborative filtering algorithm
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
SWAMI (poster session): a framework for collaborative filtering algorithm development and evaluation
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Data mining: concepts and techniques
Data mining: concepts and techniques
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
A music recommendation system based on music data grouping and user interests
Proceedings of the tenth international conference on Information and knowledge management
Refining Initial Points for K-Means Clustering
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
CIA '98 Proceedings of the Second International Workshop on Cooperative Information Agents II, Learning, Mobility and Electronic Commerce for Information Discovery on the Internet
Collaborative filtering via gaussian probabilistic latent semantic analysis
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Flycasting: Using Collaborative Filtering to Generate a Playlist for Online Radio
WEDELMUSIC '01 Proceedings of the First International Conference on WEB Delivering of Music (WEDELMUSIC'01)
Clustering Approach for Hybrid Recommender System
WI '03 Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
A music recommender based on audio features
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Accurate web recommendations based on profile-specific url-predictor neural networks
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Clustering for probabilistic model estimation for CF
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
COLLABORATIVE WEB AGENT BASED ON FRIEND NETWORK
Applied Artificial Intelligence
A collaborative filtering method based on artificial immune network
Expert Systems with Applications: An International Journal
Automatic index construction for multimedia digital libraries
Information Processing and Management: an International Journal
Music recommendation by unified hypergraph: combining social media information and music content
Proceedings of the international conference on Multimedia
Recommending friends and locations based on individual location history
ACM Transactions on the Web (TWEB)
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
Recommendation agent impact on consumer online shopping: The Movie Magic case study
Expert Systems with Applications: An International Journal
Assessing the impact of recommender agents on on-line consumer unplanned purchase behavior
Information and Management
A collaborative filtering approach to mitigate the new user cold start problem
Knowledge-Based Systems
A collaborative filtering similarity measure based on singularities
Information Processing and Management: an International Journal
A literature review and classification of recommender systems research
Expert Systems with Applications: An International Journal
A balanced memory-based collaborative filtering similarity measure
International Journal of Intelligent Systems
Information Processing and Management: an International Journal
Mining movies for song sequences with video based music genre identification system
Information Processing and Management: an International Journal
Collective intelligence as mechanism of medical diagnosis: The iPixel approach
Expert Systems with Applications: An International Journal
Cluster searching strategies for collaborative recommendation systems
Information Processing and Management: an International Journal
Novel personal and group-based trust models in collaborative filtering for document recommendation
Information Sciences: an International Journal
Incorporating group recommendations to recommender systems: Alternatives and performance
Information Processing and Management: an International Journal
Recommendations of closed consensus temporal patterns by group decision making
Knowledge-Based Systems
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A recommender system has an obvious appeal in an environment where the amount of on-line information vastly outstrips any individual's capability to survey. Music recommendation is considered a popular application area. In order to make personalized recommendations, many collaborative music recommender systems (CMRS) focus on capturing precise similarities among users or items based on user historical ratings. Despite the valuable information from audio features of music itself, however, few studies have investigated how to utilize information extracted directly from music for personalized recommendation in CMRS. In this paper, we describe a CMRS based on our proposed item-based probabilistic model, where items are classified into groups and predictions are made for users considering the Gaussian distribution of user ratings. In addition, this model has been extended for improved recommendation performance by utilizing audio features that help alleviate three well-known problems associated with data sparseness in collaborative recommender systems: user bias, non-association, and cold start problems in capturing accurate similarities among items. Experimental results based on two real-world data sets lead us to believe that content information is crucial in achieving better personalized recommendation beyond user ratings. We further show how primitive audio features can be combined into aggregate features for the proposed CRMS and analyze their influences on recommendation performance. Although this model was developed originally for music collaborative recommendation based on audio features, our experiment with the movie data set demonstrates that it can be applied to other domains.