基于超圖的關(guān)聯(lián)規(guī)則可視化方法
[Abstract]:Data visualization is an important research field in data analysis. It is widely used in the fields of transportation, medical treatment, education, business website, community, communication and so on. The purpose of data visualization analysis is to integrate human perception and cognition into the process of data processing based on visual interaction interface. Human brain intelligence and machine intelligence complement each other in order to gain insight into data. Association rule mining can extract useful, novel, and interesting frequent patterns or relationships between attributes from data. Visualizing the result of association rules can make the result of association analysis intuitionistic and easy to understand. However, there are some problems in the traditional visualization methods of association rules, such as the lack of multi-pattern association rules representation, the lack of internal information and distribution of association rules, and the need to further study the visualization methods of association rules. Based on the theoretical knowledge of hypergraph and hyper-edge, this paper studies the visualization method of association rules based on hypergraph, and designs and implements the association rules mining and visualization integrated prototype system in which users can participate. First of all, read the domestic and international visualization literature, systematically analyze the hypergraph visualization, frequent itemsets visualization, association rules visualization research status quo; Secondly, the technology of data visual analysis is described in detail. At the same time, the basic concepts of data mining, visualization, human-computer interaction and related technologies are summarized respectively. Then, based on the theory and knowledge of hypergraph, we propose an undirected hyperedge-based frequent itemset visualization algorithm and a directed hyperedge-based association rule visualization algorithm. Finally, based on the proposed visualization algorithm, a prototype system of association rule mining and visualization integration is designed and applied to the whole population data set of a province at the same time. Experimental results show that the proposed visualization method has a good display effect. The main work of this paper is as follows: 1) expatiate the data visual analysis technology to sort out the domestic and foreign related documents of data visualization, and expatiate the theory and technology of data visual analysis. First, according to hypergraph, frequent itemsets, association rules visualization literature, summarized hypergraph visualization, frequent itemset visualization, association rule visualization research status quo; Then, three main components of data visual analysis are introduced in detail: data mining, human-computer interaction, visualization related technologies, which provide a theoretical basis for further research. 2) A frequent itemset based on hypergraph is proposed. Aiming at the problems of traditional association rules visualization algorithm, such as the lack of multi-pattern association rules presentation, the lack of the internal information and distribution of association rules, the importance of attribute value is not obvious, and so on. A hypergraph based frequent itemset and association rule visualization algorithm is proposed. Firstly, based on the definition and visualization method of hypergraph and undirected hyperedge, a representation model of frequent itemsets based on hypergraph is designed, and an algorithm for visualization of frequent itemsets based on hypergraph is proposed. Then, based on the definition of directed hyperedge, the definition of BF rule graph is given. According to the different patterns of association rules, the visualization model of association rules is designed for one-to-one, one-to-many, many-to-one, many-to-many, many-to-many patterns. Combined with the "hourglass" layout structure, a hypergraph-based association rule visualization algorithm is proposed. 3) the hypergraph-based association rules mining and visualization integrated prototype system are implemented based on 2). Combined with 3D technology and human-computer interaction technology, an integrated prototype system of association rules mining and visualization based on hypergraph is implemented. The system is applied to the whole population data set of a province to show the frequent itemsets and association rules. The experimental results show that compared with the traditional visualization methods of frequent itemsets and association rules, the visualization method proposed in this paper has a good performance.
【學(xué)位授予單位】:河北師范大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:TP311.13
【相似文獻(xiàn)】
相關(guān)期刊論文 前10條
1 陳洪亮,譚建榮;基于相密度的混沌吸引子可視化方法研究[J];中國圖象圖形學(xué)報(bào);2001年05期
2 陸楓;陳傳波;盧正鼎;;基于建構(gòu)主義的教學(xué)內(nèi)容可視化研究[J];高等教育研究學(xué)報(bào);2003年01期
3 溫慶慶;;可視化技術(shù)及其應(yīng)用初探[J];科技情報(bào)開發(fā)與經(jīng)濟(jì);2007年28期
4 歐海英;張為華;趙經(jīng)成;韓玉;;設(shè)計(jì)優(yōu)化可視化研究綜述[J];系統(tǒng)仿真學(xué)報(bào);2008年20期
5 張興學(xué);黃繼鴻;張朋柱;;群體研討信息智能可視化研究[J];計(jì)算機(jī)應(yīng)用研究;2009年02期
6 郝紅星;吳玲達(dá);宋漢辰;;網(wǎng)絡(luò)社區(qū)及其鏈接可視化研究[J];計(jì)算機(jī)工程與應(yīng)用;2010年13期
7 陳楓琳;;淺談專家專長可視化方法與工具[J];中國科技信息;2013年01期
8 趙淑芬;;電力系統(tǒng)運(yùn)行狀態(tài)可視化技術(shù)綜述[J];黑龍江科技信息;2013年25期
9 Gruia-Catalin Roman;Kenneth C. Cox;陳海東;;程序的可視化:將程序映射至圖畫的技巧[J];計(jì)算機(jī)科學(xué);1993年01期
10 韓麗華,程朋根;GIS環(huán)境下面對(duì)象可視化技術(shù)與方法[J];測(cè)繪通報(bào);2001年07期
相關(guān)會(huì)議論文 前10條
1 陳洪亮;譚建榮;;基于相密度的混沌吸引子可視化方法研究[A];中國圖象圖形學(xué)會(huì)第十屆全國圖像圖形學(xué)術(shù)會(huì)議(CIG’2001)和第一屆全國虛擬現(xiàn)實(shí)技術(shù)研討會(huì)(CVR’2001)論文集[C];2001年
2 吳曉莉;史美萍;;晶體生長實(shí)驗(yàn)流場(chǎng)數(shù)據(jù)的可視化研究[A];’2004系統(tǒng)仿真技術(shù)及其應(yīng)用學(xué)術(shù)交流會(huì)論文集[C];2004年
3 余弦;吳鋒;;一種危險(xiǎn)品運(yùn)輸車輛監(jiān)控信息可視化方法[A];浙江省信號(hào)處理學(xué)會(huì)2011學(xué)術(shù)年會(huì)論文集[C];2011年
4 柳佳佳;;可視化與地圖學(xué)[A];中國地理信息系統(tǒng)協(xié)會(huì)第四次會(huì)員代表大會(huì)暨第十一屆年會(huì)論文集[C];2007年
5 吳鵬;李思昆;;基于本體論的社會(huì)網(wǎng)絡(luò)信息建模與可視化方法[A];中國計(jì)算機(jī)圖形學(xué)進(jìn)展2008--第七屆中國計(jì)算機(jī)圖形學(xué)大會(huì)論文集[C];2008年
6 張毅;華一新;曹亞妮;曹一冰;;面向談判劃界的國界信息可視化方法研究與實(shí)踐[A];第四屆“測(cè)繪科學(xué)前沿技術(shù)論壇”論文精選[C];2012年
7 劉曉平;李書杰;石慧;;規(guī)律維問題初探[A];計(jì)算機(jī)技術(shù)與應(yīng)用進(jìn)展——全國第17屆計(jì)算機(jī)科學(xué)與技術(shù)應(yīng)用(CACIS)學(xué)術(shù)會(huì)議論文集(下冊(cè))[C];2006年
8 周獻(xiàn)中;顧衛(wèi)江;;一個(gè)基于過程的可視化決策系統(tǒng)設(shè)計(jì)與實(shí)現(xiàn)[A];西部開發(fā)與系統(tǒng)工程——中國系統(tǒng)工程學(xué)會(huì)第12屆年會(huì)論文集[C];2002年
9 趙志強(qiáng);阮宗才;陸祖宏;;一種三維腦圖像數(shù)據(jù)遠(yuǎn)程可視化新方法[A];第十三屆全國圖象圖形學(xué)學(xué)術(shù)會(huì)議論文集[C];2006年
10 季浩;李書杰;劉曉平;;規(guī)律維的建模與可視化方法研究[A];全國第19屆計(jì)算機(jī)技術(shù)與應(yīng)用(CACIS)學(xué)術(shù)會(huì)議論文集(下冊(cè))[C];2008年
相關(guān)重要報(bào)紙文章 前1條
1 本報(bào)記者 李聞芝;可視化技術(shù)推動(dòng)制品品質(zhì)提升[N];中國化工報(bào);2005年
相關(guān)博士學(xué)位論文 前10條
1 雋立然;面向個(gè)人基因組變異的功能注釋與可視化方法研究[D];哈爾濱工業(yè)大學(xué);2015年
2 盧德寶;復(fù)雜地形條件下基于電阻率法的對(duì)地可視化監(jiān)測(cè)技術(shù)研究[D];南京大學(xué);2015年
3 馮朝路;心臟組織分割與可視化關(guān)鍵算法研究[D];東北大學(xué);2014年
4 李杰;地理觀測(cè)數(shù)據(jù)時(shí)空可視化方法研究[D];天津大學(xué);2015年
5 甘Oz;基于參數(shù)可視化的裂變堆中子學(xué)精細(xì)建模方法研究[D];中國科學(xué)技術(shù)大學(xué);2016年
6 鄧燁;基于屬性偏序可視化方法的柴胡證“但見一證”理論傳承創(chuàng)新研究[D];廣州中醫(yī)藥大學(xué);2016年
7 李穎;心臟可視化研究及其在量化分析中的應(yīng)用[D];第三軍醫(yī)大學(xué);2016年
8 張雷;心臟電生理的快速仿真和交互式可視化方法研究[D];哈爾濱工業(yè)大學(xué);2013年
9 吳曉莉;面向空間遙科學(xué)實(shí)驗(yàn)的流場(chǎng)可視化技術(shù)研究[D];國防科學(xué)技術(shù)大學(xué);2007年
10 孫揚(yáng);多變?cè)W(wǎng)絡(luò)數(shù)據(jù)可視化方法研究[D];國防科學(xué)技術(shù)大學(xué);2010年
相關(guān)碩士學(xué)位論文 前10條
1 陳敏;基于元圖的關(guān)聯(lián)規(guī)則可視化方法[D];河北師范大學(xué);2015年
2 何薔;克隆代碼可視化系統(tǒng)的設(shè)計(jì)與實(shí)現(xiàn)[D];哈爾濱工業(yè)大學(xué);2015年
3 查燕平;基于非常規(guī)突發(fā)事件的人工社會(huì)可視化方法研究[D];北京理工大學(xué);2015年
4 關(guān)岳;大規(guī)模微博數(shù)據(jù)的品牌檢索與可視化[D];大連理工大學(xué);2015年
5 賀瀟磊;軟件網(wǎng)絡(luò)拓?fù)渑c參數(shù)可視化研究與分析[D];東北大學(xué);2013年
6 朱曉丹;大規(guī)模復(fù)雜電磁環(huán)境三維可視化研究與實(shí)現(xiàn)[D];電子科技大學(xué);2015年
7 吳長龍;人體肺部理想二分叉氣道樹的構(gòu)造和可視化[D];東北大學(xué);2014年
8 朱宗喜;鋼桁梁橋可視化研究[D];蘭州交通大學(xué);2015年
9 王博;鋼筋混凝土橋梁可視化及信息管理研究[D];蘭州交通大學(xué);2015年
10 田野;不同震源類型的可視化識(shí)別研究[D];廣西師范大學(xué);2015年
,本文編號(hào):2389050
本文鏈接:http://sikaile.net/kejilunwen/ruanjiangongchenglunwen/2389050.html