挖掘数据流中的频繁模式

发现数据流中的频繁项是数据流挖掘中最基本的问题之一．数据流的无限性和流动性使得传统的频繁模式挖掘算法难以适用．针对数据流的特点,在借鉴FP-growth算法的基础上．提出了一种数据流频繁模式挖掘的新方法：FP—DS算法．算法采用数据分段的思想,逐段挖掘频繁项集,用户可以连续在线获得当前的频繁项集,可以有效地挖掘所有的频繁项集,算法尤其适合长频繁项集的挖掘．通过引入误差ε,裁减了大量的非频繁项集,减少了数据的存储量,也能保证整个数据集中项目集支持度误差不超过ε.分析和实验表明算法有较好的性能．     

数据流频繁模式挖掘综述

一些先进应用如欺诈检测和趋势学习等带来了数据流频繁模式挖掘的发展。不同于静态数据,数据流挖掘面临着时空约束和项集组合爆炸等问题。对已有数据流频繁模式挖掘算法进行综述并对经典和最新算法进行分析。按照模式集合的完整程度进行分类,数据流中频繁模式分为全集模式和压缩模式。压缩模式主要包括闭合模式、最大模式、top-k模式以及三者的组合模式。不同之处是闭合模式是无损压缩的,而其他模式是有损压缩的。为了得到有趣的频繁模式,可以挖掘基于用户约束的模式。为了处理数据流中的新近事务,将算法分为基于窗口模型和基于衰减模型的方法。数据流中模式挖掘常见的还包含序列模式和高效用模式,对经典和最新算法进行介绍。最后给出了数据流模式挖掘的下一步工作。     

分布式多数据流频繁伴随模式挖掘

多数据流频繁伴随模式是指一组对象较短时间内在同一个数据流上伴随出现,并在之后一段时间以同样方式出现在其他多个数据流上.现实生活中,城市交通监控系统中的伴随车辆发现、基于签到数据的伴随人群发现、基于社交网络数据中的高频伴随词组发现热点事件等应用都可以归结为多数据流频繁伴随模式发现问题.由于数据流规模巨大且到达速度快,基于单机的集中式挖掘算法受到硬件资源的限制难以及时发现海量数据流中出现的频繁伴随模式.为此,提出面向大规模数据流频繁伴随模式发现的分布式挖掘算法.该算法首先将每个数据流划分成若干个segment片段,然后构建适合部署在分布式计算平台上的多层挖掘模型,并利用多计算节点以并行方式对大规模数据流进行处理,从而实时发现频繁伴随模式.最后,在真实数据集上进行充分实验以验证算法性能.     

数据流频繁模式挖掘算法设计

介绍了数据流频繁模式的概念和定义,提出了数据流频繁模式挖掘算法的通用数据流处理模型,详细总结了数据流频繁模式挖掘算法的三种分类方式:"窗口模型"、"结果集类型"和"结果集精确性".基于这些分类方法提出了数据流频繁模式挖掘算法的设计立方体,该立方体不仅涵盖了现有的数据流频繁模式挖掘算法,还对设计新的算法具有指导意义.基于设计立方体,分析了设计算法时应当采取的有效策略,旨在为设计新算法提供一个有力参考.最后讨论了数据流频繁模式挖掘的进一步研究工作.     

面向数据流的频繁模式挖掘研究*

数据流的无限性、高速性使得经典的频繁模式挖掘方法难以适用到数据流中。针对数据流的特点,对数据流中频繁模式挖掘问题进行了研究,提出了数据流频繁模式挖掘算法FP-SegCount。该算法将数据流分段并利用改进的FP-growth算法挖掘分段中的频繁项集,然后利用Count-Min Sketch进行项集计数。算法解决了压缩统计和计算快速高效的问题。通过实验分析,FP-SegCount算法是有效的。     

概念漂移数据流挖掘算法综述

数据流是一种新型的数据模型,具有动态、无限、高维、有序、高速和变化等特性。在真实的数据流环境中,一些数据分布是随着时间改变的,即具有概念漂移特征,称为可变数据流或概念漂移数据流。因此处理数据流模型的方法需要处理时空约束和自适应调整概念变化。对概念漂移问题和概念漂移数据流分类、聚类和模式挖掘等内容进行综述。首先介绍概念漂移的类型和常用概念改变检测方法。为了解决概念漂移问题,数据流挖掘中常使用滑动窗口模型对新近事务进行处理。数据流分类常用的模型包括单分类模型和集成分类模型,常用的方法包括决策树、分类关联规则等。数据流聚类方式通常包括基于k- means的和非基于k- means的。模式挖掘可以为分类、聚类和关联规则等提供有用信息。概念漂移数据流中的模式包括频繁模式、序列模式、episode、模式树、模式图和高效用模式等。最后详细介绍其中的频繁模式挖掘算法和高效用模式挖掘算法。     

一种数据流中的频繁模式挖掘算法

时序数据流的无限性、流动性和不规则性使得传统的频繁模式挖掘算法难以适用。针对时序数据流的特点,提出了一类特殊非规则数据流频繁模式挖掘的新算法。新算法采用时序数据分段的思想,逐段挖掘局部频繁模式,然后依据局部频繁模式有效地挖掘出所有的全局频繁模式。将新算法应用于电信领域的收入保障项目之中,结果表明,新算法具有良好的性能,能有效发现挖掘时序数据流中的频繁模式。     

数据流的频繁模式挖掘算法浅析

介绍了数据流的定义和特点及数据流频繁模式的基本概念。针对数据流的特性,讨论分析了目前国内外数据流频繁模式挖掘算法、算法特性及应用情况,最后展望了数据流频繁模式挖掘的进一步研究工作。     

CBC-DS:基于频繁闭模式的数据流分类算法

基于关联规则的分类算法通常根据频繁模式生成类关联规则,但频繁模式挖掘易遭受组合爆炸问题,影响算法效率.并且数据流的出现也对分类算法提出了新的挑战.相对于频繁模式,频繁闭模式的数目较少,挖掘频繁闭模式的算法通常具有较高的效率.为此,提出了一种高效的基于频繁闭模式的数据流分类算法-CBC-DS.主要贡献在于:1)提出了一种基于逆文法顺序FP-Tree的频繁闭项集单遍挖掘过程,用于挖掘类关联规则,该过程采用了一种混合项顺序搜索策略以满足数据流挖掘的单遍性需求,并采用位图技术提高效率;2)提出了"自支持度"概念,用于筛选规则以提高算法分类精度.实验表明,位图技术能够提高算法速度2倍以上,利用自支持度能够提高算法平均精度0.5%左右;最终CBC-DS算法的平均分类精度比经典算法CMAR高1%左右,并且CBC-DS算法的规则挖掘速度远快于CMAR算法.     

界标窗口数据流频繁模式挖掘特性

随着数据流应用领域的不断扩大,数据流频繁模式挖掘技术逐渐成为数据挖掘领域研究的核心问题。对DSFPM算法进行研究和改进,提出了一种基于界标窗口的数据流频繁模式挖掘算法DSMFP_LW。该算法实现了单边扫描数据流;利用扩展的前缀模式树存储全局临界频繁模式,实现数据增量更新。通过对比实验,结果证明DSMFP_LW算法有较好的时间开销和空间利用率,优于经典的Lossy Counting算法,适合数据流频繁模式挖掘。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

基于QTE的蒙古文显示机制研究与实现

蒙古语言是中国蒙古族使用的通用语言,由于蒙古文区别于其他文字的书写方式和其自身变形机制等特点,在很多通用的文字处理引擎中都不被支持。在嵌入式产品开发与应用领域中Linux加QTE已经成为流行方式。该文给出了一种在QTE环境上实现基于标准Unicode的蒙古文点阵显示和变形算法, 并自定义了支持蒙古文的QTE组件,扩展了QTE功能,为在Linux加QTE方式的嵌入式体系结构中处理蒙古文提供了一种解决方法。