Adapting Recommendations to Contextual Changes Using Hierarchical Hidden Markov Models

Recommender systems help users find items of interest by tailoring their recommendations to users' personal preferences. The utility of an item for a user, however, may vary greatly depending on that user's specific situation or the context in which the item is used. Without considering these changes in preferences, the recommendations may match the general… (More)