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A Visual Interaction Framework for Dimensionality Reduction Based Data Exploration [article]

Marco Cavallo, Çağatay Demiralp
2018 arXiv   pre-print
Here we propose a visual interaction framework to improve dimensionality-reduction based exploratory data analysis.  ...  Dimensionality reduction is a common method for analyzing and visualizing high-dimensional data. However, reasoning dynamically about the results of a dimensionality reduction is difficult.  ...  ACKNOWLEDGMENTS The authors thank Paulo Freire for inspiring the name "Praxis."  ... 
arXiv:1811.12199v1 fatcat:ced7siqaqrazbhniryb3yevkxq

Visual Analytics: A Comprehensive Overview

Wenqiang Cui
2019 IEEE Access  
As such, a novel categorization of visual-analytics applications from a technical perspective is proposed, which is based on the dimensionality of visualization and the type of interaction.  ...  Visual analytics employs interactive visualization to integrate human judgment into algorithmic data-analysis processes.  ...  To facilitate collaboration and information sharing in visual analytics, building a web-based framework for visual analytics is a potential research direction.  ... 
doi:10.1109/access.2019.2923736 fatcat:bvjajbzleneedjmgwgzz7opsdm

CloudVista: Visual Cluster Exploration for Extreme Scale Data in the Cloud [chapter]

Keke Chen, Huiqi Xu, Fengguang Tian, Shumin Guo
2011 Lecture Notes in Computer Science  
Experimental study shows this framework is effective and efficient for visually exploring clustering structures for extreme scale datasets stored in the cloud.  ...  The CloudVista framework aims to explore the entire large data stored in the cloud with the help of the data structure visual frame and the previously developed VISTA visualization model.  ...  Cluster visualization is also a dimensionality reduction problem in the sense that it maps the original data space to the two dimensional visual space.  ... 
doi:10.1007/978-3-642-22351-8_21 fatcat:sisldc27rvgrnf6y27akgkeqxi

Combining Automated and Interactive Visual Analysis of Biomechanical Motion Data [chapter]

Scott Spurlock, Remco Chang, Xiaoyu Wang, George Arceneaux, Daniel F. Keefe, Richard Souvenir
2010 Lecture Notes in Computer Science  
We present a framework for combining automated and interactive visual analysis techniques for use on high-resolution biomechanical data.  ...  Our multi-view framework allows investigators to simultaneously view a low-dimensional embedding, motion segment clustering, and 3D visual representation of the data side-by-side.  ...  Acknowledgements We wish to thank Elizabeth Brainerd and the XROMM group at Brown University for the insight, infrastructure, and data that enabled us to explore this research within the context of the  ... 
doi:10.1007/978-3-642-17274-8_55 fatcat:d7uyu3brpbcsbhfm3bofybxwyq

Parallel Coordinates Guided High Dimensional Transfer Function Design [article]

Xin Zhao
2013 arXiv   pre-print
Parallel coordinate plot (PCP), as a powerful visualization tool, can efficiently display high-dimensional geometry and accurately analyze multivariate data.  ...  reduction methods, to obtain sophisticated data classification as transfer function for volume rendering.  ...  Dimension reduction and projection, on the other hand, provide a similarity based layout for the data, where the distance in high-dimensional space is embedded into a lower-dimensional space.  ... 
arXiv:1305.4583v2 fatcat:s3zne6acx5esnlxrcakwxd4b34

Adaptive Mapping of Sound Collections for Data-driven Musical Interfaces

Gerard Roma, Owen Green, Pierre Alexandre Tremblay
2019 Zenodo  
In this paper we propose novel framework for automatic creation of interactive sound spaces from sound collections using feature learning and dimensionality reduction.  ...  Descriptor spaces have become an ubiquitous interaction paradigm for music based on collections of audio samples.  ...  t-SNE t-SNE [21] is a more recent, popular algorithm which is specialized for visualizing high-dimensional data.  ... 
doi:10.5281/zenodo.3672975 fatcat:ufxzj37egza4bgxg3utnaatrbq

FUn: a framework for interactive visualizations of large, high-dimensional datasets on the web

Daniel Probst, Jean-Louis Reymond, Jonathan Wren
2017 Bioinformatics  
Other solutions enable the web-based visualization of big data only through data reduction or statistical representations.  ...  Results: Here we present FUn, a framework consisting of a client (Faerun) and server (Underdark) module, facilitating the creation of web-based, interactive 3D visualizations of large datasets, enabling  ...  Conclusion In summary, we believe that FUn, a framework facilitating easy web-based and interactive visualization of large, high-dimensional datasets, is a powerful tool to provide an additional route  ... 
doi:10.1093/bioinformatics/btx760 pmid:29186333 fatcat:44hptt6v2rbfbieomywvgz3ozi

Visual Hierarchical Dimension Reduction for Exploration of High Dimensional Datasets [article]

J. Yang, M.O. Ward, E.A. Rundensteiner, S. Huang
2003 EUROVIS 2005: Eurographics / IEEE VGTC Symposium on Visualization  
In this paper we propose a new approach to handling high dimensional data, named Visual Hierarchical Dimension Reduction (VHDR), that addresses these drawbacks.  ...  Our case study of applying VHDR to a real data set supports our belief that this approach is effective in supporting the exploration of high dimensional data sets.  ...  David Brown, who gave us many valuable suggestions for this work. Figure (a) shows the automatically generated hierarchy. Figure (b) shows the detail of a cluster after brushing and rotation.  ... 
doi:10.2312/vissym/vissym03/019-028 fatcat:hijoqwhs3jd7nadb4jjmryxlwq

Integrating Information Visualization and Dimensionality Reduction: A pathway to Bridge the Gap between Natural and Artificial Intelligence

Diego H. Peluffo-Ordóñez
2021 Tecno Lógicas  
A suitable alternative to simultaneously involve these two concepts—and then bridging the gap between natural and artificial intelligence—is bringing together the fields of dimensionality reduction (DimRed  ...  ) and information visualization (InfoVis).  ...  Dimensionality reduction (DimRed) DimRed is a key tool for artificial intelligence tasks-more specifically machine learningthat involve high dimensional data sets.  ... 
doi:10.22430/22565337.2108 fatcat:6h2gtcujrffmdj42prg6jtyt7y

Graphical neuroimaging informatics: Application to Alzheimer's disease

John Darrell Van Horn, Ian Bowman, Shantanu H. Joshi, Vaughan Greer
2013 Brain Imaging and Behavior  
The Informatics Visualization for Neuroimaging (INVIZIAN) framework allows one to graphically display image and meta-data information from sizeable collections of neuroimaging data as a whole using a dynamic  ...  In this article, we illustrate the utility of INVIZIAN for simultaneous exploration and mining a large collection of extracted cortical surface data arising in clinical neuroimaging studies of patients  ...  Visual Hierarchical Dimension Reduction (VHDR) (Yang, Ward et al. 2003) constructs and arranges dimensions into a hierarchy, presented as a radial interface facilitating user exploration of dimensional  ... 
doi:10.1007/s11682-013-9273-9 pmid:24203652 pmcid:PMC4012008 fatcat:ws5vsn5sizb53kkzdspyri3vru

Visualizing High-Dimensional Data: Advances in the Past Decade

Shusen Liu, Dan Maljovec, Bei Wang, Peer-Timo Bremer, Valerio Pascucci
2017 IEEE Transactions on Visualization and Computer Graphics  
Visualization plays an important role in exploring such datasets. We provide a comprehensive survey of advances in high-dimensional data visualization over the past 15 years.  ...  We aim at providing actionable guidance for data practitioners to navigate through a modular view of the recent advances, allowing the creation of new visualizations along the enriched information visualization  ...  Third, developing frameworks to extract as well as to simplify "skeletons" from high-dimensional data can be extremely useful for visual data abstraction and exploration (e.g., [SMC07]).  ... 
doi:10.1109/tvcg.2016.2640960 pmid:28113321 fatcat:3xb2npz44fgxzpfueum5hhso5u

A Survey of Visual Analytics Techniques and Applications: State-of-the-Art Research and Future Challenges

Guo-Dao Sun, Ying-Cai Wu, Rong-Hua Liang, Shi-Xia Liu
2013 Journal of Computer Science and Technology  
Visual analytics employs interactive visualizations to integrate users' knowledge and inference capability into numerical/algorithmic data analysis processes.  ...  The growing popularity of visual analytics in recent years creates the need for a broad survey that reviews and assesses the recent developments in the field.  ...  TimeSeer [39] is a useful visualization tool for exploring the high-dimensional time series data.  ... 
doi:10.1007/s11390-013-1383-8 fatcat:reurwsabkvdehjv7ub2oj6jqgi

Visual Analytics of Complex Genomics Data to Guide Effective Treatment Decisions

Quang Nguyen, Nader Khalifa, Pat Alzamora, Andrew Gleeson, Daniel Catchpoole, Paul Kennedy, Simeon Simoff
2016 Journal of Imaging  
comparison and user-centric interaction and exploration based on feature selection.  ...  In addition to the traditional way to visualise data, we utilise the Unity3D platform for developing a smooth and interactive visual presentation of the information.  ...  Dimensionality Reduction Dimensionality reduction is needed to generate new features for patients and to project them into a lower dimensional similarity space for visualisation.  ... 
doi:10.3390/jimaging2040029 fatcat:npvraafuhbawpeuzmtfl6cfkta

Information visualisation and machine learning: characteristics, convergence and perspective

Benoît Frénay, Bruno Dumas
2016 The European Symposium on Artificial Neural Networks  
On the other hand, machine learning can provide powerful algorithms for clustering, dimensionality reduction, data cleansing, outlier detection, etc.  ...  This paper highlight opportunities to collaborate for experts in both fields.  ...  A relatively comparable example is the article of De Bie et al. [21] which presents a framework for more meaningful data projections for high-dimensional data.  ... 
dblp:conf/esann/FrenayD16 fatcat:wera3pv3gbalnj3gownkze6p5u

Multivariate volume visualization through dynamic projections

Shusen Liu, Bei Wang, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Valerio Pascucci
2014 2014 IEEE 4th Symposium on Large Data Analysis and Visualization (LDAV)  
ABSTRACT We propose a multivariate volume visualization framework that tightly couples dynamic projections with a high-dimensional transfer function design for interactive volume visualization.  ...  We assume that the complex, high-dimensional data in the attribute space can be well-represented through a collection of low-dimensional linear subspaces, and embed the data points in a variety of 2D views  ...  ABSTRACT We propose a multivariate volume visualization framework that tightly couples dynamic projections with a high-dimensional transfer function design for interactive volume visualization.  ... 
doi:10.1109/ldav.2014.7013202 dblp:conf/ldav/LiuWTBP14 fatcat:j7vcl6uul5eslfopaw3mausyv4
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