Communications of the ACM
Controlled experiments on the web: survey and practical guide
Data Mining and Knowledge Discovery
Item-Based and User-Based Incremental Collaborative Filtering for Web Recommendations
EPIA '09 Proceedings of the 14th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
Build your own music recommender by modeling internet radio streams
Proceedings of the 21st international conference on World Wide Web
Dimensions as Virtual Items: Improving the predictive ability of top-N recommender systems
Information Processing and Management: an International Journal
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Recommender Systems are a hot application area these days, made popular by well known web sites. The problem of predicting user preferences is very demanding from the data mining algorithm design point of view, but it also poses challenges to evaluation and monitoring. Moreover, there is a lot of information that can be exploited, from clickstreams and background information to musical content and social interaction. As data grows and recommendation requests must be answered in a split second, online and agile solutions must be implemented. In this talk we will give a brief introduction to binary recommender systems, describe a particular hybrid application to music recommendation - from algorithm to online evaluation, and refer to context aware and online recommender algorithms.