A Framework for Collaborative, Content-Based and Demographic Filtering
Artificial Intelligence Review - Special issue on data mining on the Internet
Adaptive interfaces for ubiquitous web access
Communications of the ACM - The Adaptive Web
User Modeling for Adaptive News Access
User Modeling and User-Adapted Interaction
A case study on the effectiveness of recommendations in the mobile internet
Proceedings of the third ACM conference on Recommender systems
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Consumers and businesses have access to vast stores of information on the Internet, ranging from newspapers, shopping catalogs, restaurant guides, classified ads, jobs listings, dating services to discussion groups and e-mail. All this information is typically accessible only while users are in front of a computer at home or in an office. Wireless devices allow unprecedented access to information from any location at any time. The presentation of this information must be tailored to the constraints of mobile devices. Small screens, slower connections, high latency and limited input capabilities present new challenges. Agents that learn user's preferences and select information for the user are a convenience when displaying information on a 19-inch desktop monitor accessed over a broadband connection; they are essential on a handheld wireless device. This paper summarizes commercially deployed systems using machine learning methods for personalizing mobile information delivery.