Music analysis tasks, such as structure identification and modulation detection, are tedious when performed manually due to the complexity of the common music notation (CMN). Fully automated analysis instead misses human intuition about relevance. …
Manually investigating sheet music collections is challenging for music analysts due to the magnitude and complexity of underlying features, structures, and contextual information. However, applying sophisticated algorithmic methods would require …
Explainable AI aims to render model behavior understandable by humans, which can be seen as an intermediate step in extracting causal relations from correlative patterns. Due to the high risk of possible fatal decisions in image-based clinical …
Despite the success of contextualized language models on various NLP tasks, it is still unclear what these models really learn. In this paper, we contribute to the current efforts of explaining such models by exploring the continuum between function …
Visual analytics systems integrate interactive visualizations and machine learning to enable expert users to solve complex analysis tasks. Applications combine techniques from various fields of research and are consequently not trivial to evaluate. …
Mixed-initiative visual data analysis processes are characterized by the co-adaptation of users and systems over time. As the analysis progresses, both actors – users and systems – gather information, update their analysis behavior, and work on …
Communication consists of both meta-information as well as content. Currently, the automated analysis of such data often focuses either on the network aspects via social network analysis or on the content, utilizing methods from text-mining. However, …
Mixed-initiative visual analytics systems support collaborative human-machine decision-making processes. However, many multiobjective optimization tasks, such as topic model refinement, are highly subjective and context-dependent. Hence, systems need …
Linguistic insight in the form of high-level relationships and rules in text builds the basis of our understanding of language. However, the data-driven generation of such structures often lacks labeled resources that can be used as training data for …
Visual analytics enables the coupling of machine learning models and humans in a tightly integrated workflow, addressing various analysis tasks. Each task poses distinct demands to analysts and decision-makers. In this survey, we focus on one …