Spark框架结合分布式KNN分类器的网络大数据分类处理方法

针对现有大数据分类方法难以满足大数据应用中时间和储存空间的限制,提出了一种基于Apache Spark框架的大数据并行多标签K最近邻分类器设计方法。为了通过使用其他内存操作来减轻现有MapReduce方案的成本消耗,首先,结合Apache Spark框架的并行机制将训练集划分成若干分区;然后在Map阶段找到待预测样本每个分区的K近邻,进一步在reduce阶段根据map阶段的结果确定最终的K近邻;最后并行地对近邻的标签集合进行聚合,通过最大化后验概率输出待预测样本的目标标签集合。在PokerHand等四个大数据分类数据集上进行实验,提出方法取得了较低的汉明损失,证明了其有效性。     

基于Hadoop 的分布式朴素贝叶斯文本分类

云计算的诞生,有效地解决了海量数据集的存储和分析处理。在云计算实现的开源Hadoop分布式系统集群上,使用MapReduce并行编程模型,设计并实现了一种对TFIDF改进的分布式朴素贝叶斯文本分类算法。实验结果表明,基于Hadoop框架的分布式朴素贝叶斯文本自动分类器不仅能处理节点失效,同时具有高效性和易扩展性的优势。     

云计算环境下朴素贝叶斯文本分类算法的实现

采用分布式编程MapReduce模型研究了文本统一格式预处理、训练、测试以及分类等基于朴素贝叶斯文本分类算法主要计算过程的MapReduce并行化方法,并在Hadoop云计算平台进行了实验。实验结果表明：朴素贝叶斯文本分类算法MapReduce并行化后在Hadoop云计算平台上部署运行,具有较好的加速比,对中文网页文本分类识别率达到了86%。     

基于MapReduce的并行贝叶斯分类算法的设计与实现

针对现代大规模文本文档分类在单机计算机上训练和测试过程计算时间长,本文设计和实现了一种基于MapReduce架构的并行贝叶斯文本分类算法。在用普通PC搭建的Hadoop集群上研究实验,结果表明,基于MapReduce架构的贝叶斯文本自动分类算法处理大规模的文档自动分类时,在保证分类效果的情况下,并能获得接近线性的加速比。     

一种大数据环境中分布式辅助关联分类算法

在很多现实的分类应用中,新数据的类标需要由领域专家最终确定,而分类器的分类结果仅起辅助作用.另外,随着大数据所隐含价值越发被人们重视,分类器的训练会从面向单一数据集逐渐过渡到面向分布式空间数据集,大数据环境下辅助分类也将成为未来分类应用的重要分支.然而,现有的分类研究缺乏对此类应用的关注.大数据环境中的辅助分类面临以下3个问题:1) 训练集是分布式大数据集;2) 在空间上,训练集所包含的各局部数据源的类别分布不尽相同;3) 在时间上,训练集是动态变化的,会发生类别迁移现象.在考虑以上问题的基础上,提出一种大数据环境中分布式辅助关联分类方法.该方法首先给出一种大数据环境中分布式关联分类器构建算法,在该算法中,通过横向加权考虑分类数据集在空间上的类别分布差异,并给出"前件空间支持度-相关系数"的度量框架,改进关联分类算法面对不平衡数据的性能缺陷;然后,给出一种基于适应因子的辅助关联分类器动态调整方法,能够在分类器应用过程中充分利用领域专家实时反馈的结果对分类器进行动态调整,以提升其面向动态数据集的分类性能,减缓分类器的退化和重新训练的频率.实验结果表明,该方法能够面向分布式数据集较快地训练出有较高分类准确率的关联分类器,并在数据集不断扩充变化时提升分类性能,是一种有效的大数据环境中辅助分类应用方法.     

基于Spark的压缩近邻算法

K-近邻(K-Nearest Neighbors,K-NN)是一种懒惰学习算法,用K-NN对数据分类时,不需要训练分类模型。K-NN算法的优点是思想简单、易于实现;缺点是计算量大,原因是在对测试样例进行分类时,其需要计算测试样例与训练集中每一个训练样例之间的距离。压缩近邻算法(Condensed Nearest Neighbors,CNN)可以克服K-NN算法的不足。但是,在面对大数据集时,由于自身的迭代计算特性,CNN的运算效率会变得非常低。针对这一问题,提出一种名为Spark CNN的压缩近邻算法。在大数据环境下,与基于MapReduce的CNN算法相比,Spark CNN的效率大幅提高,在5个大数据集上的实验证明了这一结论。     

嵌入式无线局域网适配器的设计与实现

针对单词簇上训练朴素贝叶斯文本分类器概率估计偏差较大所导致的分类精度较低问题,在概率分布聚类算法得到的单词簇的基础上,根据单词与簇间互信息建立有序单词子序列,采用有放回随机抽样对序列构造规模相当的样本集,并将估计出的参数的平均值作为训练得到的参数对未知文本进行分类.公共文本实验数据集上的实验结果表明,该文提出的训练方法相对于传统的朴素贝叶斯分类器训练方法能够获得更高的分类精度且过程相对简单.     

基于Bootstrap Averaging的贝叶斯分类算法

针对单词簇上训练朴素贝叶斯文本分类器概率估计偏差较大所导致的分类精度较低问题.在使用概率分布聚类算法得到的单词簇的基础上,根据单词与簇间互信息建立有序单词子序列,采用有放回随机抽样对单词序列构造规模相当的样本集并将估计出的参数的平均值作为训练得到的最终参数对未知文本进行分类.公共文本实验数据集上的实验结果表明,提出的训练方法相对于传统的朴素贝叶斯分类器训练方法能够获得更高的分类精度且过程相对简单.     

基于树桩网络的贝叶斯文本分类算法

分析贝叶斯文本分类算法的不足,提出相应的改进算法。放宽朴素贝叶斯文本分类模型中的属性独立性假设,采用一种改进的基于贝叶斯定理的文本分类模型“树桩网络”,改进朴素贝叶斯文本分类模型。实验证明,改进后的文本分类模型适合于文本分类的需要,改善了原有分类器的性能。     

基于自助平均的朴素贝叶斯文本分类器

针对单词簇上训练朴素贝叶斯文本分类器概率估计偏差较大所导致的分类精度较低问题，在概率分布聚类算法得到的单词簇的基础上，根据单词与簇间互信息建立有序单词子序列，采用有放回随机抽样对序列构造规模相当的样本集，并将估计出的参数的平均值作为训练得到的参数对未知文本进行分类。公共文本实验数据集上的实验结果表明，该文提出的训练方法相对于传统的朴素贝叶斯分类器训练方法能够获得更高的分类精度且过程相对简单。     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.     

A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.     

The Distributed Time-Triggered Simulation Scheme: Core Principles and Supporting Execution Engine

Distributed real-time simulation is a young technology field but its practice is under increasing demands. In recent years the author and his collaborators have been establishing a new approach called the distributed time-triggered simulation (DTS) scheme which is conceptually simple and easy to use but widely applicable. The concept was initiated in the course of developing a new-generation object-oriented real-time programming scheme called the time-triggered message-triggered object (TMO) programming scheme. Some fundamental issues inherent in distributed real-time simulation that were learned during recent experimental studies are discussed along with some approaches for resolving the issues. An execution engine developed to support both the TMOs engaged in control computation and the TMOs engaged in DTS is also discussed along with its possible extensions that will enable significantly larger-scale DTSs.     

Software-Konfigurationsmanagement in großen Softwareprojekten

Zusammenfassung Mit zunehmender Größe der Softwaresysteme verschärfen sich die für die Software-Herstellung typischen Probleme: Beherrschen großer Objektmengen, Erhalten der Systemkonsistenz, Kontrolle der ständigen Änderungseinflüsse und Gewährleisten einer langen Lebensdauer. Die Disziplin Konfigurationsmanagement bildet den methodischen Ansatz, diese Probleme besser zu beherrschen. Software-Konfigurationsmanagement faßt die Herstellung von Softwaresystemen als eine Abfolge von kontrollierten Änderungen an gesicherten Zwischen- und Endergebnissen auf. Dargestellt werden die Objekte und Funktionen des Software-Konfigurationsmanagements sowie die hierfür in großen Software-Projekten benötigten Methoden, Instanzen und Hilfsmittel.     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and     

Editorial:Brain-machine interface(BMI) and cyborg intelligence

正Brain-machine interfaces(BMIs)aim at building a direct communication pathway between the brain and an external device,and represent an area of research where significant progress has been made during the past decade.Based on BMIs,mind information can be read out by neural signals to control     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and overseas to the world’s scientific circles,especially to stimulate     

SCIENCE CHINA Information Sciences SUBJECT INDEX TO VOLUME 57(2014)

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Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and overseas to the world’s scientific circles,especially to stimulate