本文選題：大數(shù)據(jù) + 可視化��； 參考：《計(jì)算機(jī)應(yīng)用》2017年07期

【摘要】：大數(shù)據(jù)的來臨增強(qiáng)了可視化的重要性�？梢暬治鐾诰蛉祟悓�(duì)于信息的認(rèn)知能力與優(yōu)勢,將人、機(jī)有機(jī)融合,借助人機(jī)交互高效洞悉大數(shù)據(jù)背后的信息與規(guī)律,是大數(shù)據(jù)分析的重要方法。針對(duì)大數(shù)據(jù)數(shù)據(jù)量大、維度高、多來源、多形態(tài)等特點(diǎn)論述了大規(guī)模數(shù)據(jù)、流數(shù)據(jù)、非結(jié)構(gòu)和異構(gòu)數(shù)據(jù)的可視化方法。首先討論了大規(guī)模數(shù)據(jù)的可視化技術(shù):1)采用分而治之的原則將大問題分解成較小的任務(wù)并采用并行處理的方式解決以提高處理的速度;2)通過聚合、采樣、多分辨表示的方法進(jìn)行數(shù)據(jù)約簡;3)針對(duì)高維數(shù)據(jù)選擇若干個(gè)視圖,在多個(gè)角度下生成不同的可視化結(jié)果。然后針對(duì)監(jiān)控型、疊加型兩類流數(shù)據(jù)探討了流數(shù)據(jù)的可視化過程。最后闡述了非結(jié)構(gòu)化數(shù)據(jù)以及異構(gòu)性數(shù)據(jù)的可視化技術(shù)�？傊�,可視化能夠克服計(jì)算機(jī)自動(dòng)化分析方法的劣勢與不足,整合計(jì)算機(jī)的分析能力和人們對(duì)信息的感知能力,有效地洞悉大數(shù)據(jù)背后的信息與智慧,但其理論研究成果也非常有限,同時(shí)面臨著數(shù)據(jù)規(guī)模大、動(dòng)態(tài)變化、維度高、多源異構(gòu)等方面的挑戰(zhàn),這些也逐漸成為今后的大數(shù)據(jù)可視化研究的熱點(diǎn)與方向。
[Abstract]:Big data's arrival enhanced the importance of visualization. Visual analysis is an important method to explore the cognitive ability and advantage of human being for information, to combine human and machine organically, and to understand the information and law behind big data with the help of human-computer interaction. Aiming at big data's characteristics of large amount of data, high dimension, multi-source and multi-form, this paper discusses the visualization methods of large-scale data, stream data, unstructured data and heterogeneous data. In this paper, we first discuss the visualization technique of large-scale data: 1) decomposing large problems into smaller tasks using the principle of divide-and-conquer and using parallel processing to improve the speed of processing. The method of multi-resolution representation is used for data reduction. (3) several views are selected for high-dimensional data, and different visualization results are generated from multiple angles. Then, the visualization process of stream data is discussed for two kinds of stream data: monitor type and superposition type. Finally, the visualization technology of unstructured data and heterogeneous data is introduced. In short, visualization can overcome the disadvantages and shortcomings of computer automated analysis methods, integrate the analytical ability of computers and people's perception of information, and effectively discern the information and wisdom behind big data. However, its theoretical research results are also very limited. At the same time, it faces the challenges of large scale of data, dynamic change, high dimension, multi-source heterogeneity and so on. These also become the focus and direction of the visualization research of big data in the future.
【作者單位】： 寧波工程學(xué)院電子與信息工程學(xué)院;計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)國家重點(diǎn)實(shí)驗(yàn)室(浙江大學(xué));甘肅農(nóng)業(yè)大學(xué)信息科學(xué)技術(shù)學(xué)院;
【基金】：國家自然科學(xué)基金資助項(xiàng)目(61422211)~~
【分類號(hào)】：TP311.13

【參考文獻(xiàn)】

相關(guān)期刊論文 前2條

1 李偉;周峰;朱煒;徐瑞華;;軌道交通網(wǎng)絡(luò)客流大數(shù)據(jù)可視化研究[J];中國鐵路;2015年02期

2 任磊;杜一;馬帥;張小龍;戴國忠;;大數(shù)據(jù)可視分析綜述[J];軟件學(xué)報(bào);2014年09期

【共引文獻(xiàn)】

相關(guān)期刊論文 前10條

1 崔迪;郭小燕;陳為;;大數(shù)據(jù)可視化的挑戰(zhàn)與最新進(jìn)展[J];計(jì)算機(jī)應(yīng)用;2017年07期

2 楊波;劉文彬;付沙;周航軍;謝建全;;教育大數(shù)據(jù)時(shí)代的教學(xué)新模式——量化教學(xué)[J];內(nèi)江師范學(xué)院學(xué)報(bào);2017年06期

3 肖祥林;周春容;;大數(shù)據(jù)在公路工程質(zhì)量監(jiān)控中的應(yīng)用與挑戰(zhàn)[J];微型電腦應(yīng)用;2017年06期

4 張健欽;王鵬宇;杜明義;;一種城市公交線網(wǎng)分布的可視化分析方法[J];測繪通報(bào);2017年05期

5 陳興蜀;曾雪梅;王文賢;邵國林;;基于大數(shù)據(jù)的網(wǎng)絡(luò)安全與情報(bào)分析[J];工程科學(xué)與技術(shù);2017年03期

6 郭鵬;;收益管理中基于大數(shù)據(jù)倉庫的需求無約束估計(jì):框架與挑戰(zhàn)[J];大數(shù)據(jù);2017年03期

7 王衛(wèi);楊巋;馬力;;可視化在校園一卡通建設(shè)中的應(yīng)用[J];華中師范大學(xué)學(xué)報(bào)(自然科學(xué)版);2017年S1期

8 陳曉慧;萬剛;張偉;廖雨婷;李鋒;;面向敘事結(jié)構(gòu)的地理空間情報(bào)可視分析方法[J];測繪科學(xué)技術(shù)學(xué)報(bào);2017年01期

9 管翔輝;;基于大數(shù)據(jù)的分析與挖掘問題研究[J];數(shù)字通信世界;2017年05期

10 吳，

本文編號(hào)：1835366