Titlebook: User Modeling, Adaptation and Personalization; 23rd International C Francesco Ricci,Kalina Bontcheva,Séamus Lawless Conference proceedings

MULTI

Nonporous

Counteracting Anchoring Effects in Group Decision Making decision bias in the context of group decision scenarios. On the basis of the results of a user study in the domain of software requirements prioritization we discuss results regarding the optimal time when preference information of other users should be disclosed to the current user. Furthermore,

睨視

Gifting as a Novel Mechanism for Personalized Museum and Gallery Interpretationet the diverse needs of individual visitors. However, increased personalization can mean that the sociality of museum visits is overlooked. We present a new approach to resolving the tension between the personal and the social that invites visitors themselves to personalize and gift interpretations

陰險(xiǎn)

synchronous

Neutral-Spine

Towards a Recommender Engine for Personalized Visualizationsy people understand them. However, creating them requires specific expertise of the domain and underlying data to determine the right representation. Although there are rules that help generate them, the results are too broad to account for varying user preferences. To tackle this issue, we propose

波動(dòng)

heterogeneous

大漩渦

Where to Next? A Comparison of Recommendation Strategies for Navigating a Learning Object Repository houses over 1250 educational resources. The proposed approaches stem from three basic strategies: recommendations based on resource metadata, user behavior, and alignment to academic standards. An evaluation from subject experts suggests that usage-based recommendations are best aligned with teache

寬敞

Diagrammatic Student Models: Modeling Student Drawing Performance with Deep Learningnts’ learning and increase their engagement, developing student models to dynamically support drawing holds significant promise. To this end, we introduce ., which reason about students’ drawing trajectories to generate a series of predictions about their conceptual knowledge based on their evolving