Group Modeling: Selecting a Sequence of Television Items to Suit a Group of Viewers
User Modeling and User-Adapted Interaction
Incorporating contextual information in recommender systems using a multidimensional approach
ACM Transactions on Information Systems (TOIS)
Progress in information retrieval
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
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Personal information needs depend on long-term interests and on current and future situations (contexts): people are mainly interested in weather forecasts for future destinations, and in toy advertisements when a child's birthday approaches. As computer capabilities for being aware of users' contexts grow, the users' willingness to set manually rules for context-based information retrieval will decrease. Thus computers must learn to associate user contexts with information needs in order to collect and present information proactively. This work presents experiments with training a SVM (Support Vector Machines) classifier to learn user information needs from calendar information.