直接从空间数据中挖掘频繁模式

为简化空间频繁模式挖掘的预处理步骤并提高挖掘效率, 提出一种可以直接以空间矢量和栅格图层作为输入的挖掘算法FISA(fast intersect spatial Apriori)。该算法利用图层求交和面积计算操作实现谓词集支持度计数进而实现频繁谓词集和关联规则挖掘。相对于基于事务空间关联规则挖掘算法, FISA不需要预先进行空间数据事务化处理, 并且所得结果均有对应图层, 便于实现结果的可视化; 相对于其他基于空间分析的挖掘算法, FISA支持空间数据的矢量和栅格格式, 且引入了快速求交方法以保证其可伸缩性。实验结果表明该算法可以直接从空间数据中高效正确地挖掘出频繁模式。     

Some challenges of integrating spatial and non-spatial datasets using a geographical information system

Geographical Information Systems or GIS are becoming useful tools in making strategic decisions in a variety of government and business activities in areas such as housing, healthcare, land use, natural resources, environmental monitoring, public health, transportation, retail, and routing. This usefulness emanates from the capability of GIS to present a large amount of data in a short period of time on a map, using a geographical coordinate system. In most cases, spatial datasets required for GIS mapping are already available free from many governmental agencies. GIS use more of computing technology than geographical concepts, however, the capabilities of GIS software did not reach the level of simplicity encountered in most software used on a daily basis. Most organizations perform GIS analysis on their data without getting involved with the mapping technology. A typical GIS analyst faces various challenges while incorporating non-spatial dataset to spatial dataset in order to present resulting dataset on a geographical map. In this paper, we present some data manipulation complexities that are encountered while using a GIS software to provide spatial twists to a large user dataset. We also provide ways to facilitate the data manipulation process through a practical example of asthma epidemiology. The solutions will be beneficial to many GIS users in varieties of industries.     

基于条件互信息的多维时间序列图模型

在多维时间序列的图模型中引入信息论方法, 提出了多维时间序列中各分量之间直接线性联系存在性的互信息检验．定义了线性条件互信息图, 图中的结点表示多维时间序列的分量, 结点间的边表示各分量之间存在的直接线性相依关系．提出了分量之间条件线性联系存在性的信息论检验方法．图中边的存在性用基于线性条件互信息的统计量检验, 统计量的显著性用置换检验决定．应用到实例中的结果表明本文的方法能迅速准确的捕捉各分量之间的直接线性联系.     

Exploratory factor analysis revisited: How robust methods support the detection of hidden multivariate data structures in IS research

Exploratory factor analysis is commonly used in IS research to detect multivariate data structures. Frequently, the method is blindly applied without checking if the data fulfill the requirements of the method. We investigated the influence of sample size, data transformation, factor extraction method, rotation, and number of factors on the outcome. We compared classical exploratory factor analysis with a robust counterpart which is less influenced by data outliers and data heterogeneities. Our analyses revealed that robust exploratory factor analysis is more stable than the classical method.     

Visualizing “typical” and “exotic” Internet traffic data

The threat of cyber attacks motivates the need to monitor Internet traffic data for potentially abnormal behavior. Due to the enormous volumes of such data, statistical process monitoring tools, such as those traditionally used on data in the product manufacturing arena, are inadequate. “Exotic” data may indicate a potential attack; detecting such data requires a characterization of “typical” data. We devise some new graphical displays, including a “skyline plot,” that permit ready visual identification of unusual Internet traffic patterns in “streaming” data, and use appropriate statistical measures to help identify potential cyberattacks. These methods are illustrated on a moderate-sized data set (135,605 records) collected at George Mason University.     

空间关联规则的增量维护

为了得到有趣且有效的空间关联规则通常需要多次执行挖掘操作,可以使用增量维护算法来提高挖掘效率。然而,能够直接使用空间数据的关联规则增量更新算法尚属空白。为解决这一问题,对挖掘阈值改变和空间数据集更新后通过筛选或增量挖掘等方法实现规则维护的策略进行了分析,并提出适用于支持度阈值减小和空间图层增加这两类情况的增量挖掘算法——ISA。ISA算法不依赖于空间事务表的构建与更新,可以直接使用空间图层作为输入数据。在基于实际数据的实验中,采用ISA算法所得结果与类Apriori算法一致,耗时则相对缩短20.0%至71.0%;此外,对1372772条规则进行了基于筛选的更新,耗时低于0.1s。实验结果表明,所提出的空间关联规则增量维护策略和算法是可行、正确且高效的。     

基于GPU的地震剖面图形快速绘制算法

地震剖面图的绘制是二维地震数据可视化的基础。目前基于通用绘制引擎的地震剖面图绘制是在CPU上实现的,随着地震数据规模越来越大,传统绘制方法的绘制效率已经不能达到交互效率的要求,因此提出了一种地震剖面图快速绘制算法。该算法将地震数据的绘制和GPGPU技术相结合,利用GPU强大的并行计算能力实现图形光栅化处理。实验表明,在保证绘制效果的前提下,该方法极大地提高了绘制效率。     

多尺度空间判别性概率潜在语义分析的场景分类

传统潜在语义分析(Latent Semantic Analysis, LSA)方法无法获得场景目标空间分布信息和潜在主题的判别信息。针对这一问题提出了一种基于多尺度空间判别性概率潜在语义分析(Probabilistic Latent Semantic Analysis, PLSA)的场景分类方法。首先通过空间金字塔方法对图像进行空间多尺度划分获得图像空间信息,结合PLSA模型获得每个局部块的潜在语义信息;然后串接每个特定局部块中的语义信息得到图像多尺度空间潜在语义信息;最后结合提出的权值学习方法来学习不同图像主题间的判别信息,从而得到图像的多尺度空间判别性潜在语义信息,并将学习到的权值信息嵌入支持向量基(Support Vector Machine, SVM)分类器中完成图像的场景分类。在常用的三个场景图像库(Scene-13、Scene-15和Caltech-101)上的实验表明,该方法平均分类精度比现有许多state-of-art方法均优。验证了其有效性和鲁棒性。     

Survey of glyph-based visualization techniques for spatial multivariate medical data

In this survey article, we review glyph-based visualization techniques that have been exploited when visualizing spatial multivariate medical data. To classify these techniques, we derive a taxonomy of glyph properties that is based on classification concepts established in information visualization. Considering both the glyph visualization as well as the interaction techniques that are employed to generate or explore the glyph visualization, we are able to classify glyph techniques into two main groups: those supporting pre-attentive and those supporting attentive processing. With respect to this classification, we review glyph-based techniques described in the medical visualization literature. Based on the outcome of the literature review, we propose design guidelines for glyph visualizations in the medical domain.     

A statistical approach to knowledge acquisition for expert systems

Classical expert systems are rule based, depending on predicates expressed over attributes and their values. In the process of building expert systems, the attributes and constants used to interpret their values need to be specified. Standard techniques for doing this are drawn from psychology, for instance, interviewing and protocol analysis. This paper describes a statistical approach to deriving interpreting constants for given attributes. It is also possible to suggest the need for attributes beyond those given.The approach for selecting an interpreting constant is demonstrated by an example. The data to be fitted are first generated by selecting a representative collection of instances of the narrow decision addressed by a rule, then making a judgement for each instance, and defining an initial set of potentially explanatory attributes. A decision rule graph plots the judgements made against pairs of attributes. It reveals rules and key instances directly. It also shows when no rule is possible, thus suggesting the need for additional attributes. A study of a collection of seven rule based models shows that the attributes defined during the fitting process improved the fit of the final models to the judgements by twenty percent over models built with only the initial attributes.     

基于GML的多源异构空间数据集成研究

深入分析了数据格式转换、直接数据访问和数据互操作3种数据集成模式,描述了一个基于GML数据互操作模式的、多源异构空间数据集成模型,并分析了模型的运行机制和关键技术.该模型通过使用相应的GML转换接口把分布式异构空间数据源转化为统一的GML格式文档,通过集成引擎和相应的集成规则对异构空间数据进行有效的集成,实现数据共享的目的.     

基于空间索引的二维空间区域访问控制模型

针对空间数据的访问控制的特点,提出了基于空间索引的区域访问控制概念。定义了其授权和访问请求判断的规则和约束条件。给出了授权和访问请求判断的方法,建立了二维空间区域访问控制模型。     

一种求解空间数据聚类的粒子动力学演化算法*

从空间数据挖掘的基本概念出发,阐述了空间数据的特点及空间数据挖掘的常规方法,分析了用常规方法进行数据挖掘的不足,提出了一种求解空间数据聚类的粒子动力学演化算法——SDCPDEA。该方法有效地避免了用常规方法进行空间数据聚类时的缺陷,增强了聚类分析方法的灵活性和有效性。实验结果表明,对于空间数据的聚类分析问题,该算法具有很好的性能。     

Graphical causal inference and copula regression model for apple keywords by text mining

Apple is a leading company of technological evolution and innovation. This company founded and produced the Apple I computer in 1976. Since then, based on its innovative technologies, Apple has launched creative and innovative products and services such as the iPod, iTunes, the iPhone, the Apple app store, and the iPad. In many fields of academia and business, diverse studies of Apple’s technological innovation strategy have been performed. In this paper, we analyze Apple’s patents to better understand its technological innovation. We collected all applied patents by Apple until now, and applied statistics and text mining for patent analysis. By using graphical causal inference method, we created the causal relations among Apple keywords preprocessed by text mining, and then we carried out the semiparametric Gaussian copula regression model to see how the target response keyword and the predictor keywords are relating to each other. Furthermore, Gaussian copula partial correlation was applied to Apple keywords to find out the detailed dependence structure. By performing these methods, this paper shows the technological trends and relations between Apple’s technologies. This research could make contributions in finding vacant technology areas and central technologies for Apple’s R&D planning.     

空间数据挖掘技术的研究现状与发展趋势*

简要介绍了空间数据挖掘技术的产生背景和发展现状,对空间数据挖掘的体系结构和系统原型进行了概述,总结了空间数据挖掘近年来的研究方法及面临的主要问题,并对下一步的发展方向进行了展望。     

论书体汉字图形化的意境之美

中国文化博大精深,汉字经历了五千年的历史演变,逐渐由象形文字发展成为表形表意表情的符号化字形结构,而书体汉字正是以汉字图形化的视觉形式展现出来,图形化的字体形态与中国传统审美意识所强调的写意、畅神相吻合,兼具了传统与现代的美学特征,给人以审美的多元化想象,以传统艺术形式寓意了具有本土化、民族化的艺术特征。     

Analysis of multivariate medical data by face method

This paper describes the application of face pattern as a medium to illustrate to man complex computer-processed medical diagnosis. The case of a nephrotic syndrome was selected to show the mechanics of the study. First, the design of the face pattern was constructed and psychometrical experiments analyzing the resulting facial expressions were conducted. Next, the results obtained from the analysis of facial expressions based and constructed from the original findings of conventional medical methods were used to loosely predict the patient's future conditions, and the same results were compared with those of statistical procedures to test the efficiency of the method. Finally, a separate application of the method was also performed to indicate a possible effect of corticosteroid on idiopathic nephrotic syndrome.     

一种高维空间数据的子空间聚类算法

传统网格聚类方法由于没有考虑到相邻网格内的数据点对考查网格的影响,存在不能平滑聚类以及聚类边界判断不清的情况。为此提出了一种高维空间数据的子空间聚类算法,扩展了相邻聚类空间。实验结果显示,克服了传统聚类的不平滑现象,使聚类边界得以很好的处理。     

Exploring process data

With the growth of computer usage at all levels in the process industries, the volume of available data has also grown enormously, sometimes to levels that render analysis difficult. Most of this data may be characterized as historical in the sense that it was not collected on the basis of experiments designed to test specific statistical hypotheses. Consequently, the resulting datasets are likely to contain unexpected features (e.g. outliers from various sources, unsuspected correlations between variables, etc.). This observation is important for two reasons: first, these data anomalies can completely negate the results obtained by standard analysis procedures, particularly those based on squared error criteria (a large class that includes many SPC and chemometrics techniques). Secondly and sometimes more importantly, an understanding of these data anomalies may lead to extremely valuable insights. For both of these reasons, it is important to approach the analysis of large historical datasets with the initial objective of uncovering and understanding their gross structure and character. This paper presents a brief survey of some simple procedures that have been found to be particularly useful at this preliminary stage of analysis.     

The use of spatial analytical techniques to explore patterns of fire incidence: A South Wales case study

The application of mapping and spatial analytical techniques to explore geographical patterns of crime incidence is well established. In contrast, the analysis of operational incident data routinely collected by fire brigades has received relatively less research attention, certainly in the UK academic literature. The aim of this paper is to redress this balance through the application of spatial analytical techniques that permit an exploration of the spatial dynamics of fire incidents and their relationships with socio-economic variables. By examining patterns for different fire incident types, including household fires, vehicle fires, secondary fires and malicious false alarms in relation to 2001 Census of Population data for an area of South Wales, we demonstrate the potential of such techniques to reveal spatial patterns that may be worthy of further contextual study. Further research is needed to establish how transferable these findings are to other geographical settings and how replicable the findings are at different geographical scales. The paper concludes by drawing attention to the current gaps in knowledge in analysing trends in fire incidence and proposes an agenda to advance such research using spatial analytical techniques.