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A Comparative Analysis of Industry Human-AI Interaction Guidelines

With the recent release of AI interaction guidelines from Apple, Google, and Microsoft, there is clearly interest in understanding the best practices in human-AI interaction. However, industry standards are not determined by a single company, but …

Augmenting Sheet Music with Rhythmic Fingerprints

In this paper, we bridge the gap between visualization and musicology by focusing on rhythm analysis tasks, which are tedious due to the complex visual encoding of the well-established Common Music Notation (CMN). Instead of replacing the CMN, we …

DataShiftExplorer: Visualizing and Comparing Change in Multidimensional Data for Supervised Learning

In supervised learning, to ensure the model's validity, it is essential to identify dataset shifts, i.e., when the data distribution changes from the one the model encountered at the time of training. To detect such changes, a comparative analysis of …

Learning and Teaching in Co-Adaptive Guidance for Mixed-Initiative Visual Analytics

Guidance processes in visual analytics applications often lack adaptivity. In this position paper, we contribute the concept of co-adaptive guidance, building on the principles of initiation and adaptation. We argue that both the user and the system …

Towards Visual Debugging for Multi-Target Time Series Classification

Multi-target classification of multivariate time series data poses a challenge in many real-world applications (e.g., predictive maintenance). Machine learning methods, such as random forests and neural networks, support training these classifiers. …

Augmenting music sheets with harmonic fingerprints

Common Music Notation (CMN) is the well-established foundation for the written communication of musical information, such as rhythm or harmony. CMN suffers from the complexity of its visual encoding and the need for extensive training to acquire …

Framing Visual Musicology through Methodology Transfer

In this position paper, we frame the field of Visual Musicology by providing an overview of well-established musicological sub-domains and their corresponding analytic and visualization tasks. To foster collaborative, interdisciplinary research, we …

H-Matrix: Hierarchical Matrix for visual analysis of cross-linguistic features in large learner corpora

This paper presents a visualization technique for cross-linguistic error analysis in large learner corpora. H-Matrix combines a matrix, which is commonly used by linguists to investigate cross-linguistic patterns, with a tree diagram to aggregate and …

Human Trust Modeling for Bias Mitigation in Artificial Intelligence

Human-in-the-loop model-building processes are increasingly popular as they incorporate human intuition and not easily externalized domain knowledge. However, we argue that the inclusion of the human, and in particular direct model manipulations, …

lingvis.io - A Linguistic Visual Analytics Framework

We present a modular framework for the rapid-prototyping of linguistic, web-based, visual analytics applications. Our framework gives developers access to a rich set of machine learning and natural language processing steps, through encapsulating …