一种有效的序列模式增量式更新方法

针对序列模式增量式更新挖掘算法产生大量候选项集以及多次扫描数据库的问题,提出了一种有效的增量式更新算法ESPIA,该算法利用基于2-序列矩阵挖掘算法ESPE对原数据库和增加数据库一次扫描产生序列模式,通过对频繁模式和非频繁模式进行相应的剪枝减少了序列的比较和扫描次数,降低了算法时间和空间复杂度,实验证明该算法是有效和准确的。     

新的关联规则的挖掘与更新算法

关联规则挖掘已取得了许多有效的算法,但是当事物数据库发生动态变化时,或数据库保持不变,而最小支持度和最小可信度发生变化时,关联规则的高效更新仍然是个复杂的问题.给出一种新的关联规则的挖掘算法.新的算法只需扫描数据库D一次,减少了I/O次数,为关联规则的更新打下很好的基础.     

频繁模式集挖掘算法TFPDM的研究

受经典的Apriori算法思想和FP-Growth算法思想的启发,在结合两者优点的基础上提出了一种新的算法思想,它是对传统的FP-Growth算法的变形。该算法只需对数据库扫描一次,可以同时对全局和局部频繁模式集进行挖掘,减少了对发生增益数据库挖掘的费用。理论分析表明算法是有效的、可行的。     

基于幂集的关联规则挖掘算法研究

首次提出了利用幂集作为挖掘关联规则的工具,给出了基于幂集的关联规则挖掘算法。该算法有效解决了传统算法中需对数据库多次扫描的不足,实现了对数据库一次扫描就可挖掘出所有频繁集的功能。     

一种基于多数组的频繁模式挖掘算法

提出了一种新颖的频繁模式挖掘算法,该算法与现有的挖掘算法相比具有明显的优点,首先,该算法不需要产生候选项集,其次该算法具有更少的数据库扫描次数,该算法在中小型数据库上挖掘关联规则只需要扫描交易数据库一次,对于大型交易数据库的关联规则挖掘最多也只需要扫描交易数据库两次。因而,该算法与现有的频繁模式挖掘算法相比具有更高的效率。     

一种基于规则的离群挖掘算法

离群数据挖掘是指从大量数据中挖掘明显偏离、不满足一般行为模式的数据。现有的离群数据挖掘算法大多对密集的交易数据库缺乏有效的处理,文中提出了一种高效的基于规则的离群挖掘算法。该算法使用了多层最大离群支持度及最小离群兴趣度,计算1-离群条件集的幂集,并在数据结构中存储了交易标识符链表,使得扫描数据库的次数仅为一次,从而提高了挖掘的速度、效率且使得结果更具有决策意义。文中使用此算法对某一商场的部分销售数据库进行了实验,结果表明该算法能有效、迅速地发现密集数据库中的离群数据。     

基于粗糙集和单事务项组合的关联规则挖掘算法

Apriori算法必须反复地扫描数据库才能求出频繁项集,效率较低,且不支持更新挖掘。为了解决这些问题,提出了一种基于粗糙集、单事务项组合和集合运算的关联规则挖掘算法。本算法首先利用粗糙集进行属性约简,对新决策表中的每个事务进行“数据项”组合并标记地址,然后利用集合运算的方法计算支持度和置信度即可挖掘出有效规则。本算法只需要一次扫描数据库,同时有效地支持了关联规则的更新挖掘。应用实例和实验结果表明,本算法明显优于Apriori算法,是一种有效且快速的关联规则挖掘算法。     

最小频繁闭树的增量式更新算法

针对树挖掘算法产生大量频繁子树和树数据库随时间变化的问题,提出最小频繁闭树增量式更新算法以及增量式更新策略,能充分利用已有挖掘知识,无须重新运行树挖掘算法,并且只需进行一次数据库扫描操作。给出一种候选子树剪枝方法,能减少树同构判别次数,有效提高算法的运行效率。通过大量实验结果表明,该算法有效可行且效率较高。     

一种基于规则的离群挖掘算法

离群数据挖掘是指从大量数据中挖掘明显偏离、不满足一般行为模式的数据。现有的离群数据挖掘算法大多对密集的交易数据库缺乏有效的处理，文中提出了一种高效的基于规则的离群挖掘算法。该算法使用了多层最大离群支持度及最小离群兴趣度，计算1-离群条件集的幂集，并在数据结构中存储了交易标识符链表，使得扫描数据库的次数仅为一次，从而提高了挖掘的速度、效率且使得结果更具有决策意义。文中使用此算法对某一商场的部分销售数据库进行了实验，结果表明该算法能有效、迅速地发现密集数据库中的离群数据。     

一种基于布尔矩阵的关联规则快速挖掘算法

关联规则的发现是数据挖掘中的一个重要问题,其核心是频繁模式的挖掘,通常采用的APriori算法要多次扫描数据库并产生大量的候选项集,开销很大。本文采用基于布尔矩阵关联挖掘的算法,只需扫描一次数据库而且不需要链接产生候选项集,从而提高算法的效率。并通过实例说明了它是一种有效的关联规则挖掘方法。     

Call for Papers The 6^th International Conference on Grid and Cooperative Computing

Recent years have seen rapid advances in various grid-related technologies, middleware, and applications. The GCC conference has become one of the largest scientific events worldwide in grid and cooperative computing. The 6th international conference on grid and cooperative computing (GCC2007) Sponsored by China Computer Federation (CCF),Institute of Computing Technology, Chinese Academy of Sciences (ICT) and Xinjiang University ,and in Cooperation with IEEE Computer Soceity ,is to be held from August 16 to 18, 2007 in Urumchi, Xinjiang, China.     

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.     

法律信息库系统

本文分析了法律数据库的结构和特点，介绍了采用面向对象设计方法和超文本数据库技术开发和实现法律信息库系统将作为重要网络资源之一为不同用户进行法律咨询服务。     

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.     

International Journal of Automation and Computing Table of Contents

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Information for authors

正SCIENCE CHINA Information Sciences(Sci China Inf Sci),cosponsored by the Chinese Academy of Sciences and the National Natural Science Foundation of China,and published by Science China Press,is committed to publishing highquality,original results of both basic and applied research in all areas of information sciences,including computer science and technology;systems science,control science and engineering(published in Issues with odd numbers);information and communication engineering;electronic science and technology(published in Issues with even numbers).Sci China Inf Sci is published monthly in both print and electronic forms.It is indexed by Academic OneFile,Astrophysics Data System(ADS),CSA,Cabells,Current Contents/Engineering,Computing and Technology,DBLP,Digital Mathematics Registry,Earthquake Engineering Abstracts,Engineering Index,Engineered Materials Abstracts,Gale,Google,INSPEC,Journal Citation Reports/Science Edition,Mathematical Reviews,OCLC,ProQuest,SCOPUS,Science Citation Index Expanded,Summon by Serial Solutions,VINITI,Zentralblatt MATH.     

Erratum to: Fast global kernel fuzzy c-means clustering algorithm for consonant/vowel segmentation of speech signal

正Erratum to:J Zhejiang Univ-Sci C(ComputElectron)2014 15(7):551-563doi:10.1631/jzus.C1300320The original version of this article unfortunately contained mistakes.Algorithm 6 should be as follows:Algorithm 6 FGKFCM-F clustering Input:(1)X={x_1,x_2,…,x_N},,x_iR~d,i=1,2,…,N,the dataset;(2)C,1C≤N,the number of clusters;(3)ε0,the stopping criterion;     

Journal of Zhejiang University-SCIENCE C (Computers & Electronics) Total contents

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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.