A music recommender based on audio features
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic Model Estimation for Collaborative Filtering Based on Items Attributes
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
Clustering for probabilistic model estimation for CF
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
A probabilistic music recommender considering user opinions and audio features
Information Processing and Management: an International Journal - Special issue: AIRS2005: Information retrieval research in Asia
A new similarity measure for collaborative filtering to alleviate the new user cold-starting problem
Information Sciences: an International Journal
Applications of wavelet data reduction in a recommender system
Expert Systems with Applications: An International Journal
A collaborative recommender system based on probabilistic inference from fuzzy observations
Fuzzy Sets and Systems
Collaborative Recommendations Using Bayesian Networks and Linguistic Modelling
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
A collaborative filtering method based on artificial immune network
Expert Systems with Applications: An International Journal
Selecting a small number of products for effective user profiling in collaborative filtering
Expert Systems with Applications: An International Journal
International Journal of Approximate Reasoning
IPTV-VOD program recommendation system using single-scaled hybrid filtering
ISCGAV'10 Proceedings of the 10th WSEAS international conference on Signal processing, computational geometry and artificial vision
A probabilistic model for music recommendation considering audio features
AIRS'05 Proceedings of the Second Asia conference on Asia Information Retrieval Technology
Cluster ensembles in collaborative filtering recommendation
Applied Soft Computing
A latent model for collaborative filtering
International Journal of Approximate Reasoning
On the performance of high dimensional data clustering and classification algorithms
Future Generation Computer Systems
An adaptive method for the tag-rating-based recommender system
AMT'12 Proceedings of the 8th international conference on Active Media Technology
Nature-Inspired Clustering Algorithms for Web Intelligence Data
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 03
Knowledge-Based Systems
A genre-based fuzzy inference approach for effective filtering of movies
Intelligent Data Analysis
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Recommender system is a kind of web intelligence techniques to make a daily information filtering for people. In this work1, Clustering techniques have been applied to the item-based collaborative filtering framework to solve the cold start problem. It also suggests a way to integrate the content information into the collaborative filtering. Extensive experiments have been conducted on MovieLens data to analyze the characteristics of our technique. The results show that our approach contributes to the improvement of prediction quality of the item-based collaborative filtering, especially for the cold start problem.