VISMiner：一个交互式可视化数据挖掘原型系统

交互式可视化数据挖掘是利用可视化技术进行联机数据挖掘的技术。基于SOM的交互式可视化数据挖掘原型系统VISMiner的主要目的是将数据挖掘与数据可视化及OLAP进行集成,允许用户以交互的方式从SOM的标记图或距离图中选定感兴趣区域加以深入分析。     

VisualDM：一个灵活的可视化数据挖掘系统

如果要建造一个健壮的数据挖掘系统，仅仅依靠挖掘算法是不够的。目前的挖掘算法还没有完全“智能”化，所以挖掘有用的信息常常不是很有效。不过可视化技术给了我们很大的帮助，我们将挖掘算法和可视化技术结合起来，从而实现了数据挖掘系统VisualDM。     

可视化数据挖掘方法与技术

可视化数据挖掘技术是可视化技术和数据挖掘技术的有机结合,是数据挖掘技术发展的必然,它涉及到计算机图形学、图像处理、计算机辅助设计、计算机视觉及人机交互技术等多个领域：数据挖掘的可视化已由单纯的模型可视化发展到数据可视化与数据挖掘过程和结果的可视化;本文着重讨论了可视化数据挖掘的分类和相关技术,最后提出了未来的研究方向。     

一个基于OLAM的可视化数据挖掘系统原型

基于OLAM的可视化数据挖掘系统将可视化工具和数据挖掘工具融为一体,它与一般的数据挖掘系统不同,充分利用了OLAM模型沿着多个维进行挖掘,并以智能的方式与用户进行交互,可以在多维数据库的不同部位和不同的抽象级别交互地执行挖掘,以图形的方式输出结果。     

浅谈可视化数据挖掘方法与技术

数据挖掘技术的快速发展,能帮助用户更换的挖掘数据库中隐藏的丰富知识,而受挖掘技术复杂性影响,一些用户很难挖掘完整的数据,对数据的理解和掌握也比较吃力。采用图形和图像的形式,能帮助用户理解和掌握数据挖掘的结果,可视化数据挖掘技术便应运而生。     

数据挖掘中可视化技术综述

阐述了可视化技术在数据挖掘中的应用及发展前景。     

可视化数据挖掘技术研究

总结了目前数据挖掘领域中可视化方法的研究状况。结合国外先进的数据挖掘工具,分析了当前可视化数据挖掘技术的应用现状。基于可视化数据挖掘的任务和目标,阐述了可视化数据挖掘技术的发展趋势。     

数据挖掘可视化技术应用与研究

本文讨论了数据挖掘和可视化的关键技术,提出了运用在油田数据库中的一种可视化模型的设计方法。取出油田数据库的一个数据截面进行可视化,可以直观清晰的看到数据库中的频繁与例外异常模式,对提高决策的效率具有重大现实意义。     

DMVisualMiner:一个可视化数据挖掘分析平台

DMVisualMiner是将可视化技术应用于数据挖掘领域而开发的一个数据分析平台.可视化数据挖掘主要应用在4个方面数据准备阶段的可视化、模型生成阶段的可视化、结果呈现阶段的可视化、数据挖掘流程的可视化.实现了对数据挖掘各个方面的可视化,同时DMVisualMiner采用构件的设计方法,利用插件的概念增强了系统的可扩展性,设计并实现了基于XML的模型表示方法,使得DMVisualMiner能够和预言模型系统集成,并能在网络环境下发布.     

可视化数据挖掘技术的应用分析

随着社会的不断发展和科学技术的不断进步,大数据时代的到来衍生了很多新技术。其中,可视化数据挖掘技术是较为先进的一种技术,是信息化时代发展的产物。近年来,这一技术被广泛应用于各个领域,为各行各业的发展提供了便利,提高了工作效率。笔者主要阐述了可视化数据挖掘技术的相关概述,分析了可视化技术在数据挖掘技术中的应用,研究了可视化数据挖掘技术存在的问题和未来的发展趋势,以期为技术的进步提供数据支持。     

分布式数据挖掘的数据背景异质性探讨

随着计算机网络以及数据库技术的深入发展,分布式数据挖掘成为了当今的一大研究热点。然而数据分布除了存储的物理分散性,还有具有背景异质性。本文先介绍分布式数据挖掘和其面临的一些问题,然后由此引出数据背景的异质性,最后用实例研究来说明数据背景异质性对分布式数据挖掘算法的影响。     

基于数据仓库技术构建电信企业VoIP业务分析系统

介绍了电信企业VoIP业务分析系统的要求、内容及其重要性.在此基础上提出了基于数据仓库的VoIP业务分析系统框架,重点描述了建立数据仓库系统的数据提取、转换和装载,多维数据模型建立,数据挖掘应用等关键问题.     

基于动态代价敏感的数据挖掘算法探讨

信息时代的到来,数据作为信息的载体其重要性也愈加突出,随着人们对不确定数据研究的深入,代价敏感数据挖掘技术被应用于不确定数据挖掘中。本文介绍了不确定数据,分析了现有不确定数据挖掘方法,在介绍代价敏感学习的基础上,介绍了一种针对不确定数据的代价敏感决策树算法,并通过实验验证了这一算法的合理可行。     

Cultivating travellers' revisit intention to e-tourism service: the moderating effect of website interactivity

The research goals of this study were to investigate how the design and service quality of the website of the public sectors affect tourists' satisfaction and continued usage intention. We collected a sample of tourists, using a survey questionnaire, and we tested the model and hypotheses using a structural equation modelling approach. E-tourism websites have unique interactive and multimedia qualities with the potential to create experiences similar to a product trial. In total, invitation messages were mailed to 2000 members of the Taiwanese backpackers' forum, of which 256 were returned completed. The findings of this study indicate that the mission of excellence in travel services will be an important strategy in e-tourism website design; an e-tourism website that allows quick navigation is likely to attract travellers. Moreover, it is important that governments adopt a knowledge-sharing culture in their relationship strategy by developing a competence for building long-term relationships with tourists.     

Online shopping delivery delay: Finding a psychological recovery strategy by online consumer experiences

We propose a new type of psychological recovery strategy (i.e., online consumer experiences, OCEs) for online shopping delivery delay. We developed 4 types of OCEs based on the interactivity concept (low machine interactivity with low person interactivity, MI^L–PI^L; high machine interactivity with low person interactivity, MI^H–PI^L; low machine interactivity with high person interactivity, MI^L–PI^H, and high machine interactivity with high person interactivity, MI^H–PI^H). We conducted 2 studies, and 1078 online shoppers participated in this study. The results indicate that when consumers meet a delivery delay, proving them with OCEs could increase satisfaction and reduce complaint intention. Cognitive dissonance (CD) from inconsistency between OCEs and direct experience also moderates OCEs effects on satisfaction, repurchase intention, and complaint intention. Finally, desire for control (DC) and consumer susceptibility to interpersonal influence (CSII) moderate the OCEs effects on satisfaction, repurchase intention, and complaint intention: consumers with low DC and low CSII prefer MI^L–PI^L; consumers with high DC and low CSII prefer MI^H–PI^L, consumers with low DC and high CSII prefer MI^L–PI^H, and consumers with high DC and high CSII prefer MI^H–PI^H.     

Perceived interactivity leading to e-loyalty: Development of a model for cognitive–affective user responses

Novel applications of website interactivity are important to attract and retain online users. In this empirical study five designs for interactivity are examined using different web-poll interfaces. The goal of the investigation is to examine perceived interactivity in a model which includes most commonly tested cognitive elements such as efficiency and effectiveness, but augments this model with the inclusion of a cognitive–affective element for trust, and an affective element of enjoyment. More specifically, a model is created to validate the relationship of perceived interactivity (comprised of user control, user connectedness, and responsiveness of the web-poll application) to efficiency, effectiveness, trust and enjoyment, of the website. In turn, efficiency, effectiveness, trust, and enjoyment are tested for their influence on user behavioral intentions for e-loyalty. All relationships in the model are supported. In addition, exploratory evaluation of qualitative comments is conducted to investigate additional insights between the five web-poll treatments in this investigation. The research confirms the complexity of a model in which cognitive, cognitive–affective and affective elements are present, and advances knowledge on the consequences of perceived interactivity. In additional to theoretical advancements, the research has merit for web designers and online marketers regarding how to enhance interactive online web applications.     

生物信息学中基因数据可视化

科学可视化技术是进行生物数据挖掘的重要手段。本文综合介绍了主要的基因数据可视化技术 :各种基因调控网、层次树显示、信息壁技术、语义镜     

HSC: A multi-resolution clustering strategy in Self-Organizing Maps applied to astronomical observations

This work presents a strategy for the classification of astronomical objects based on spectrophotometric data and the use of unsupervised neural networks and statistical classification algorithms. Our strategy constitutes an essential part of the preparation phase of the automatic classification and parameterization algorithms for the data that are to be collected by the Gaia satellite of the European Space Agency (ESA), whose launch is foreseen for the spring of 2012. The proposed algorithm is based on a hierarchical structure of neural networks composed of various tree-structured SOM networks. The classification of possible astronomical objects (stars, galaxies, quasars, multiple objects, etc.) basically consists in the iterative segmentation of the inputs space and the ensuing generation of initial classifications and increase in classification precision by means of a refining process. Apart from providing a classification, our technique also measures the quality and precision of the classifications and segments the objects for which it cannot determine whether or not they belong to a pre-established class of astronomical objects (outliers).     

On the security of individual data

We will consider the following problem in this paper: Assume that there are numerical data (like salaries of individuals) stored in a database and some subsums of these numbers are made public or just available for persons not eligible to learn the original data. Our motivating question is: At most how many of these subsums may be disclosed such that none of the numbers can be uniquely determined from these sums. These types of problems arise in the cases when certain tasks concerning a database are done by subcontractors who are not eligible to learn the elements of the database, but naturally should be given some data to fulfill there task. In database theory such examples are called statistical databases as they are used for statistical purposes and no individual data are supposed to be obtained using a restricted list of SUM queries. This problem was originally introduced by [1], originally solved by Miller et al. [7] and revisited by Griggs [4, 5]. It was shown in [7] that no more than subsums of a given set of secure data may be disclosed without disclosing at least one of the data, which upper bound is sharp as well. To calculate a subsum, it might need some operations whose number is limited. This is why it is natural to assume that the disclosed subsums of the original elements of the database will contain only a limited number of elements, say at most . The goal of the present paper is to determine the maximum number of subsums of size at most which can be disclosed without making possible to calculate any of the individual data . The maximum is exactly determined for the case when the number of data is much larger than the size restriction .     

Sensuous Geographies: a multi-user interactive/ responsive installation

This paper discusses key issues which arose during the creation of Sensuous Geographies, a multi-user interactive/responsive installation created in 2003/4. In particular it will refer to the way in which the design of the installation was intended to draw attention to bodily sensation, facilitate collaborative interactivity between participants and bring about an emergent choreography, and to the collaborative methodology used in developing this work.