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The state of the art in integrating machine learning into visual analytics
Visual analytics systems combine machine learning or other analytic techniques with
interactive data visualization to promote sensemaking and analytical reasoning. It is through …
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 …
perspectives:(1) on what level is the interaction happening,(2) which interactive operations …
Utopian: User-driven topic modeling based on interactive nonnegative matrix factorization
Topic modeling has been widely used for analyzing text document collections. Recently,
there have been significant advancements in various topic modeling techniques, particularly …
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 …
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 …
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 …
modeling, machine learning, and data mining and is applied in business intelligence, public …
Scatternet: A deep subjective similarity model for visual analysis of scatterplots
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 …
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
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 …
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 …
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
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 …
research, it is still arduous for researchers to assess the quality of a clustering result. To …