Titlebook: User Modeling, Adaptation, and Personalization; 18th International C Paul Bra,Alfred Kobsa,David Chin Conference proceedings 2010 Springer-

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Modeling Long-Term Search Engine Usagedictive user models of search engine usage can be developed. Our findings have implications for users as well as search engine designers and marketers seeking to better understand and retain their users.

ARM

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Interaction and Personalization of Criteria in Recommender Systemsfound that the ratings of different criteria have a nonlinear interaction in some cases, for example, article novelty and subject relevance often interact. We also found that these interactions vary from user to user.

原告

Twitter, Sensors and UI: Robust Context Modeling for Interruption Management delivered is evaluated in order to minimize the impact on the user’s workflow. By carefully coupling both algorithms and user interfaces, interruptions made by the software tool can be made valuable to the user.

CUB

Collaborative Inference of Sentiments from Textsghbour collaborative approach that utilises novel models of user similarity. Our evaluation shows that our approach improves on state-of-the-art performance, and yields insights regarding datasets for which such an improvement is achievable.

legacy

AdHeat — An Influence-Based Diffusion Model for Propagating Hints to Personalize Social Adsch user with aggregated hints. Our experimental results on a large-scale social network show that AdHeat outperforms the relevance model on CTR (click through rate) by significant margins. In this talk, the algorithms employed by AdHeat and solutions to address scalability issues are presented.

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PAC

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PACT