We propose a framework for interactive and explainable machine learning that enables
users to (1) understand machine learning models;(2) diagnose model limitations using …

Visual analytics systems integrate interactive visualizations and machine learning to enable
expert users to solve complex analysis tasks. Applications combine techniques from various …

It has been widely suggested that a key goal of visualization systems is to assist decision
making, but is this true? We conduct a critical investigation on whether the activity of …

We present NEREx, an interactive visual analytics approach for the exploratory analysis of
verbatim conversational transcripts. By revealing different perspectives on multi‐party …

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 …

We present a framework that allows users to incorporate the semantics of their domain
knowledge for topic model refinement while remaining model-agnostic. Our approach …

Comparing data distributions is a core focus in descriptive statistics, and part of most data
analysis processes across disciplines. In particular, comparing distributions entails …

Argumentation Mining addresses the challenging tasks of identifying boundaries of
argumentative text fragments and extracting their relationships. Fully automated solutions do …

We present SMARTEXPLORE, a novel visual analytics technique that simplifies the
identification and understanding of clusters, correlations, and complex patterns in high …

Mixed‐initiative visual analytics systems support collaborative human‐machine decision‐
making processes. However, many multi‐objective optimization tasks, such as topic model …