Presentation 2014-03-07
Responsive Visualization for Data Mining using three.js
Aya SUZUKI, Natsumi KUGAWA, Aimi IGARASHI, Eri TSUNODA, Ko Fujimura,
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Abstract(in English) This paper presents a data visualization system for viewing complex network data. In this study, we use single-source data on TV viewing, Web access, magazine reading, and drink behavior of beer and soft drinks, collected from 3,000 subjects with their demographic profiles such as hobbies and occupations. In this paper, these complex data are modeled as property graphs in which vertices and edges have multiple properties, and the property graphs are visualized as an interactive 3D model. We implemented the system using JavaScript 3D library, three.js, and it allows users to select the properties to be visualized interactively. Selected properties are visualized instantly. We call this approach "responsive visualization" and we shows that it is useful for finding important characteristics from the complex network.
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Keyword(in English) Data mining / Visualization / Property Graph / three.js / HTML5
Paper # LOIS2013-62
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Committee LOIS
Conference Date 2014/2/28(1days)
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Registration To Life Intelligence and Office Information Systems (LOIS)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Responsive Visualization for Data Mining using three.js
Sub Title (in English)
Keyword(1) Data mining
Keyword(2) Visualization
Keyword(3) Property Graph
Keyword(4) three.js
Keyword(5) HTML5
1st Author's Name Aya SUZUKI
1st Author's Affiliation Faculty of Social Information Studies, Otsuma Women's University()
2nd Author's Name Natsumi KUGAWA
2nd Author's Affiliation Faculty of Social Information Studies, Otsuma Women's University
3rd Author's Name Aimi IGARASHI
3rd Author's Affiliation Faculty of Social Information Studies, Otsuma Women's University
4th Author's Name Eri TSUNODA
4th Author's Affiliation Faculty of Social Information Studies, Otsuma Women's University
5th Author's Name Ko Fujimura
5th Author's Affiliation Faculty of Social Information Studies, Otsuma Women's University
Date 2014-03-07
Paper # LOIS2013-62
Volume (vol) vol.113
Number (no) 479
Page pp.pp.-
#Pages 6
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