23 citations · 34 across the 4 of their papers we have counts for
4 papers
Know What Not To Know: Users' Perception of Abstaining Classifiers
Andrea Papenmeier, Daniel Hienert, Yvonne Kammerer +2
Machine learning systems can help humans to make decisions by providing decision suggestions (i.e., a label for a datapoint). However, individual datapoints do not always provide e…
How Accurate Does It Feel? -- Human Perception of Different Types of Classification Mistakes
Andrea Papenmeier, Dagmar Kern, Daniel Hienert +2
Supervised machine learning utilizes large datasets, often with ground truth labels annotated by humans. While some data points are easy to classify, others are hard to classify, w…
SaL-Lightning Dataset: Search and Eye Gaze Behavior, Resource Interactions and Knowledge Gain during Web Search
Christian Otto, Markus Rokicki, Georg Pardi +9
The emerging research field Search as Learning investigates how the Web facilitates learning through modern information retrieval systems. SAL research requires significant amounts…
Predicting Knowledge Gain during Web Search based on Multimedia Resource Consumption
Christian Otto, Ran Yu, Georg Pardi +7
In informal learning scenarios the popularity of multimedia content, such as video tutorials or lectures, has significantly increased. Yet, the users' interactions, navigation beha…