Title:
Visualize It-Wise! An Iteration-Wise Computational Framework for Real-Time Visual Analytics
Visualize It-Wise! An Iteration-Wise Computational Framework for Real-Time Visual Analytics
dc.contributor.author | Choo, Jaegul | |
dc.contributor.author | Lee, Changhyun | |
dc.contributor.author | Park, Haesun | |
dc.contributor.corporatename | Georgia Institute of Technology. College of Computing | en_US |
dc.contributor.corporatename | Georgia Institute of Technology. School of Computational Science and Engineering | en_US |
dc.contributor.corporatename | Georgia Institute of Technology. School of Electrical and Computer Engineering | en_US |
dc.date.accessioned | 2013-04-01T14:44:14Z | |
dc.date.available | 2013-04-01T14:44:14Z | |
dc.date.issued | 2013 | |
dc.description | Research areas: Information Visualization, Visual Analytics | en_US |
dc.description.abstract | Abstract Visual analytics has been gaining increasing interest due to its fascinating characteristic that leverages both humans’ visual perception and the power of computing. Although various computational methods are being proposed, they do not properly support visual analytics. One of the biggest obstacles towards their real-time visual analytic integration is their high computational complexity. As a way to tackle this problem, this paper presents an iteration-wise computational framework, motivated by the fact that most advanced computational methods work by refining the solution iteratively. By visually delivering the results for each iteration to users, the proposed framework enables users to quickly acquire the information that the computational method provides as well as the ability to interact with them in real time. We show the benefits of the proposed framework by using various dimension reduction and clustering methods. | en_US |
dc.embargo.terms | null | en_US |
dc.identifier.uri | http://hdl.handle.net/1853/46593 | |
dc.language.iso | en_US | en_US |
dc.publisher | Georgia Institute of Technology | en_US |
dc.relation.ispartofseries | CSE Technical Reports; GT-CSE-13-01 | en_US |
dc.subject | Clustering | en_US |
dc.subject | Constant time | en_US |
dc.subject | Dimension reduction | en_US |
dc.subject | Global illumination | en_US |
dc.subject | Information visualization | en_US |
dc.subject | k-means | en_US |
dc.subject | Latent Dirichlet allocation | en_US |
dc.subject | Principal component analysis | en_US |
dc.subject | Radiosity | en_US |
dc.subject | t-SNE | en_US |
dc.subject | Visual analytics | en_US |
dc.title | Visualize It-Wise! An Iteration-Wise Computational Framework for Real-Time Visual Analytics | en_US |
dc.type | Text | |
dc.type.genre | Technical Report | |
dspace.entity.type | Publication | |
local.contributor.author | Park, Haesun | |
local.contributor.corporatename | College of Computing | |
local.contributor.corporatename | School of Computational Science and Engineering | |
local.relation.ispartofseries | College of Computing Technical Report Series | |
local.relation.ispartofseries | School of Computational Science and Engineering Technical Report Series | |
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relation.isOrgUnitOfPublication | 01ab2ef1-c6da-49c9-be98-fbd1d840d2b1 | |
relation.isSeriesOfPublication | 35c9e8fc-dd67-4201-b1d5-016381ef65b8 | |
relation.isSeriesOfPublication | 5a01f926-96af-453d-a75b-abc3e0f0abb3 |