Title:
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
relation.isAuthorOfPublication 92013a6f-96b2-4ca8-9ef7-08f408ec8485
relation.isOrgUnitOfPublication c8892b3c-8db6-4b7b-a33a-1b67f7db2021
relation.isOrgUnitOfPublication 01ab2ef1-c6da-49c9-be98-fbd1d840d2b1
relation.isSeriesOfPublication 35c9e8fc-dd67-4201-b1d5-016381ef65b8
relation.isSeriesOfPublication 5a01f926-96af-453d-a75b-abc3e0f0abb3
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