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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (3): 21-28    DOI: 10.11925/infotech.2096-3467.2017.03.03
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Visualization of Coalition Data Based on Multi View Cooperation
Xuefeng Shen(),Yongzhen Ke,Nan Yao
School of Computer Science & Software Engineering, Tianjin Polytechnic University, Tianjin 300387, China
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Abstract  

[Objective] This paper proposes a data visualization model to retrieve, analyze and present historical records from a data coalition, aiming to improve the knowledge discovery. [Methods] We constructed a model for the visual data analysis system, and then used a big data platform to examine its feasibility. [Results] The proposed system could analyze massive historical data and then support the decision making procedures. [Limitations] The current visual analysis result views could be further improved by adding more chart templates. [Conclusions] The proposed system could analyze historical data from the library alliance and provide valuable information for decision makers.

Key wordsCoalition Data      Big Data      Visibility Analysis      Borrowed Records     
Received: 14 November 2016      Published: 25 September 1985

Cite this article:

Xuefeng Shen, Yongzhen Ke, Nan Yao. Visualization of Coalition Data Based on Multi View Cooperation. Data Analysis and Knowledge Discovery, 2017, 1(3): 21-28.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.03.03     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2017/V1/I3/21

[1] 任磊, 杜一, 马帅, 等. 大数据可视分析综述[J]. 软件学报, 2014, 25(9): 1909-1936.
[1] (Ren Lei, Du Yi, Ma Shuai, et al.Visual Analytics Towards Big Data[J]. Journal of Software, 2014, 25(9): 1909-1936.)
[2] 贺德方, 曾建勋. 基于语义的馆藏资源深度聚合研究[J]. 中国图书馆学报, 2012, 38(200): 79-87.
[2] (He Defang, Zeng Jianxun.Study on In-depth Integration of Library Collections Based on Semantics[J]. Journal of Library Science in China. 2012, 38(200): 79-87.)
[3] 赵迎春. 灰色关联分析在高校图书馆图书采购中的应用[J]. 农业图书情报学刊, 2016, 28(9): 114-118.
[3] (Zhao Yingchun.Application of Grey Relation Analysis Method in the College Libraies’ Books Acquisition[J]. Journal of Library and Information Sciences in Agriculture. 2016, 28(9): 114-118.)
[4] 尹纪军. 基于改进遗传神经网络的图书采购系统研究[D]. 镇江: 江苏大学, 2007.
[4] (Yin Jijun.Research on Book Purchasing System Based on Improved Genetic Neural Network [D]. Zhen Jiang: Jiangsu University, 2007.)
[5] 李媛, 胡蓉. 模糊综合评判法在高校图书馆文献采购中的应用[J]. 农业图书情报学刊, 2014, 26(5): 72-75.
[5] (Li Yuan, Hu Rong.The Application of Fuzzy Comprehensive Evaluation Method in the Document Purchasing of University Library[J]. Journal of Library and Information Sciences in Agriculture. 2014, 26(5): 72-75.)
[6] 迟春佳, 毛志勇. 基于数据挖掘的高校图书馆图书采购计划辅助决策研究[J]. 现代情报, 2009, 29(7): 108-110.
[6] (Chi Chunjia, Mao Zhiyong.Research on Assistant Decision- making in Formulating University Library Book Purchasing Plan Based on Data Mining[J]. Journal of Modern Information, 2009, 29(7): 108-110.)
[7] 冯娜. 浅议基于数据挖掘的高校图书馆购书计划[J]. 农业图书情报学刊, 2016, 28(4): 112-114.
[7] (Feng Na.A Brief Discussion of University Library’s Book Procurement Plan Based on Data Mining[J]. Journal of Library and Information Sciences in Agriculture, 2016, 28(4): 112-114.)
[8] 赵海森, 吕琳, 薄志涛. 面向层次化数据的变分圆形树图[J]. 软件学报, 2016, 27(5): 1103-1113.
[8] (Zhao Haisen, Lǚ Lin, Bo Zhitao.Variational Circular Treemaps for Hierarchical Data[J]. Journal of Software, 2016, 27(5): 1103-1113.)
[9] Schulz H J.Treevis. net: A Tree Visualization Reference[J]. IEEE Computer Graphics and Applications, 2011. 31(6): 11-15.
[10] Schulz H J, Schumann H.Visualizing Graphs—A Generalized View[C]//Proceedings of the Conference on Information Visualization (IV 2006). Washington, USA: IEEE Computer Society, 2006, 166-173.
[11] Tak S, Cockburn A.Enhanced Spatial Stability with Hilbert and Moore Treemaps[J]. IEEE Transactions on Visualization and Computer, 2013. 19(1): 141-148.
[12] Lam H C, Dinov I D.Hyperbolic Wheel: A Novel Hyperbolic Space Graph Viewer for Hierarchical Information Content[J]. ISRN Computer Graphics, 2012(6): 487-493.
[13] Ham F V, Wijk J V.Beamtrees: Compact Visualization of Large Hierarchies[J]. Information Visualization. 2003. 2(1): 31-39.
[14] 陈谊, 甄远刚, 胡海云, 等. 一种层次结构中多维属性的可视化方法[J]. 软件学报, 2016, 27(5): 1091-1102.
[14] (Chen Yi, Zhen Yuangang, Hu Haiyun, et al.Visualization Technique for Multi-Attrbute in Hierarchical Structure[J]. Journal of Software, 2016, 27(5): 1091-1102.)
[15] Chen Y, Zhang X Y, Feng Y C, et al.Sunburst with Ordered Nodes Based on Hierarchical Clustering: A Visual Analyzing Method for Associated Hierarchical Pesticide Residue Data[J]. Journal of Visualization, 2015. 18(2): 237-254.
[16] Bring Data to Life with SVG, Canvas and HTML[EB/OL]. [2016-11-04]..
[17] Vizuly. Weighted Tree [EB/OL]. [2016-11-04]. .
[18] NPasha. Bipartite Graph [EB/OL]. [2016-11-04]. .
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