Ranking Companion integrates six complementary item-selection methods with model-driven active learning in a visual analytics interface to support iterative personalized ranking creation via known-item judgments.
Dudley and Per Ola Kristensson
3 Pith papers cite this work. Polarity classification is still indexing.
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A user study with 20 participants shows that closeness between sketches, annotations, and language in a shared space helps disambiguate multimodal queries, leading to the concept of proximity semantics for data exploration systems.
A literature review shows that constructs for appropriate reliance on AI are fragmented, presents three views on the topic, and calls for consensus on objective metrics to enable better comparisons across studies.
citing papers explorer
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Ranking Companion: A Visual Analytics Approach to Item-Based Ranking with Hybrid Item Selection
Ranking Companion integrates six complementary item-selection methods with model-driven active learning in a visual analytics interface to support iterative personalized ranking creation via known-item judgments.
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From 'Here' to 'There': Exploring Proximity Semantics in Multimodal Data Exploration
A user study with 20 participants shows that closeness between sketches, annotations, and language in a shared space helps disambiguate multimodal queries, leading to the concept of proximity semantics for data exploration systems.
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From Trust to Appropriate Reliance: Measurement Constructs in Human-AI Decision-Making
A literature review shows that constructs for appropriate reliance on AI are fragmented, presents three views on the topic, and calls for consensus on objective metrics to enable better comparisons across studies.