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Found 15 papers, 5 papers with code
MOSAIC: Multimodal Multistakeholder-aware Visual Art Recommendation
Visual art (VA) recommendation is complex, as it has to consider the interests of users (e. g. museum visitors) and other stakeholders (e. g. museum curators).
Modeling User Preferences via Brain-Computer Interfacing
Previous approaches have tackled these incredibly challenging tasks using a variety of behavioral signals, from dwell-time to click-through data, and computational models of visual correspondence to these behavioral signals.
Impact of Design Decisions in Scanpath Modeling
We show that even small variations of these design parameters have a noticeable impact on standard evaluation metrics such as DTW or Eyenalysis.
EyeFormer: Predicting Personalized Scanpaths with Transformer-Guided Reinforcement Learning
From a visual perception perspective, modern graphical user interfaces (GUIs) comprise a complex graphics-rich two-dimensional visuospatial arrangement of text, images, and interactive objects such as buttons and menus.
Artful Path to Healing: Using Machine Learning for Visual Art Recommendation to Prevent and Reduce Post-Intensive Care
Staying in the intensive care unit (ICU) is often traumatic, leading to post-intensive care syndrome (PICS), which encompasses physical, psychological, and cognitive impairments.
The Elements of Visual Art Recommendation: Learning Latent Semantic Representations of Paintings
Artwork recommendation is challenging because it requires understanding how users interact with highly subjective content, the complexity of the concepts embedded within the artwork, and the emotional and cognitive reflections they may trigger in users.
Adapting User Interfaces with Model-based Reinforcement Learning
Adapting an interface requires taking into account both the positive and negative effects that changes may have on the user.
Model-based Reinforcement Learning
reinforcement-learning
+1
Query Abandonment Prediction with Recurrent Neural Models of Mouse Cursor Movements
Most successful search queries do not result in a click if the user can satisfy their information needs directly on the SERP.
My Mouse, My Rules: Privacy Issues of Behavioral User Profiling via Mouse Tracking
This paper aims to stir debate about a disconcerting privacy issue on web browsing that could easily emerge because of unethical practices and uncontrolled use of technology.
Understanding Visual Saliency in Mobile User Interfaces
For graphical user interface (UI) design, it is important to understand what attracts visual attention.
Human or Machine? It Is Not What You Write, But How You Write It
Online fraud often involves identity theft.
Learning Efficient Representations of Mouse Movements to Predict User Attention
Tracking mouse cursor movements can be used to predict user attention on heterogeneous page layouts like SERPs.
A Price-Per-Attention Auction Scheme Using Mouse Cursor Information
There is thus an opportunity to devise a more effective ad pricing paradigm, in which ads are paid only if they are actually noticed.
Evaluating the effects of interactivity in a post-editing workbench
This paper describes the field trial and subsequent evaluation of a post-editing workbench which is currently under development in the EU-funded CasMaCat project.
