How Hierarchical Topics Evolve in Large Text Corpora

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Towards Better Analysis of Deep Convolutional Neural Networks (2016, methodology): “In CNNVis, we employ the layout algorithm in TextFlow [12, 13] to calculate the position of each node (e.”
Online Visual Analytics of Text Streams (2015, methodology): “We also provide the following interactions to explore the complex evolutionary clustering results from multiple perspectives in addition to the interactions described in [12] (e.g., details on demand, collapsing/ expanding time steps, splitting/merging topic bars, and changing focus).”
On Building Online Visualization Maps for News Data Streams by Means of Mathematical Optimization (2018, unknown): “45 Finally, the approach is online, such that the plots for the ﬁrst T 0 (cid:2) 1 periods are already available, and we need to construct the plots in periods T 0 , . . . , T , where new words may appear, using the mentioned criteria.”
Towards better analysis of machine learning models: A visual analytics perspective (2017, background): “In addition to an explosion of research on better understanding of learning results [6, 7, 8, 9, 10, 11, 12, 13, 14], researchers have paid increasing attention to leveraging interactive visualizations to better understand and iteratively improve a machine learning model.”