The state of the art in integrating machine learning into visual analytics

A Endert, W Ribarsky, C Turkay… - Computer graphics …, 2017‏ - Wiley Online Library
Visual analytics systems combine machine learning or other analytic techniques with
interactive data visualization to promote sensemaking and analytical reasoning. It is through …

Interactive clustering: A comprehensive review

J Bae, T Helldin, M Riveiro, S Nowaczyk… - ACM Computing …, 2020‏ - dl.acm.org
In this survey, 105 papers related to interactive clustering were reviewed according to seven
perspectives:(1) on what level is the interaction happening,(2) which interactive operations …

Utopian: User-driven topic modeling based on interactive nonnegative matrix factorization

J Choo, C Lee, CK Reddy… - IEEE transactions on …, 2013‏ - ieeexplore.ieee.org
Topic modeling has been widely used for analyzing text document collections. Recently,
there have been significant advancements in various topic modeling techniques, particularly …

Survey on the analysis of user interactions and visualization provenance

K Xu, A Ottley, C Walchshofer, M Streit… - Computer Graphics …, 2020‏ - Wiley Online Library
There is fast‐growing literature on provenance‐related research, covering aspects such as
its theoretical framework, use cases, and techniques for capturing, visualizing, and …

The human is the loop: new directions for visual analytics

A Endert, MS Hossain, N Ramakrishnan… - Journal of intelligent …, 2014‏ - Springer
Visual analytics is the science of marrying interactive visualizations and analytic algorithms
to support exploratory knowledge discovery in large datasets. We argue for a shift from a …

The state‐of‐the‐art in predictive visual analytics

Y Lu, R Garcia, B Hansen, M Gleicher… - Computer Graphics …, 2017‏ - Wiley Online Library
Predictive analytics embraces an extensive range of techniques including statistical
modeling, machine learning, and data mining and is applied in business intelligence, public …

Scatternet: A deep subjective similarity model for visual analysis of scatterplots

Y Ma, AKH Tung, W Wang, X Gao… - IEEE transactions on …, 2018‏ - ieeexplore.ieee.org
Similarity measuring methods are widely adopted in a broad range of visualization
applications. In this work, we address the challenge of representing human perception in the …

Facetto: Combining unsupervised and supervised learning for hierarchical phenotype analysis in multi-channel image data

R Krueger, J Beyer, WD Jang, NW Kim… - IEEE transactions on …, 2019‏ - ieeexplore.ieee.org
Facetto is a scalable visual analytics application that is used to discover single-cell
phenotypes in high-dimensional multi-channel microscopy images of human tumors and …

An approach to supporting incremental visual data classification

JGS Paiva, WR Schwartz, H Pedrini… - IEEE transactions on …, 2014‏ - ieeexplore.ieee.org
Automatic data classification is a computationally intensive task that presents variable
precision and is considerably sensitive to the classifier configuration and to data …

XCluSim: a visual analytics tool for interactively comparing multiple clustering results of bioinformatics data

S L'Yi, B Ko, DH Shin, YJ Cho, J Lee, B Kim, J Seo - BMC bioinformatics, 2015‏ - Springer
Background Though cluster analysis has become a routine analytic task for bioinformatics
research, it is still arduous for researchers to assess the quality of a clustering result. To …