Titlebook: User Modeling, Adaptation and Personalization; 22nd International C Vania Dimitrova,Tsvi Kuflik,Geert-Jan Houben Conference proceedings 201

白杨

损坏

Bridle

Eye Tracking to Understand User Differences in Visualization Processing with Highlighting Interventirent highlighting interventions designed to facilitate visualization usage. We then link these results to task performance in order to provide insights on how to design user-adaptive information visualization systems. Our results show how the least effective intervention manifests itself as a distra

时代错误

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0302-9743 l recommendations; user experience; user awareness and control; Affective aspects; UMAP underpinning by psychology models; privacy; perceived security and trust; behavior change and persuasion.978-3-319-08785-6978-3-319-08786-3Series ISSN 0302-9743 Series E-ISSN 1611-3349

CRANK

Modelling Long Term Goalss of evidence to validate the usefulness of our Goal Model to represent three long term health-related goals. It shows that the Goal Interface is usable and aids people in setting their long term goals.

Bridle

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Factual

Hybrid Recommendation in Heterogeneous Networksth relations. Compared to prior work with shorter metapaths, we show that a hybrid composed of components using longer metapaths yields improvements in recommendation diversity without loss of accuracy on social tagging datasets.

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Time-Sensitive User Profile for Optimizing Search Personlizationeature. In order to evaluate our approach, we model the user profile according to data collected from Twitter. Then, we rerank initial search results accurately to the user profile. Moreover, we proved the significance of adding a temporal feature by comparing our method with baselines models that does not consider the user profile dynamics.