约束数据库中的分解与无损连接

约束数据模型作为一种新的数据库模型正受到广泛关注，为了约束数据库的有效应用，需要研究的设计。为此对密序约束数据中的变量独立函数依赖，模式设计，分解，无损连接规范表示概念给出了严格的定义。给出了计算规范表示的算法，它能保持约束元 组的变量独立，并证明了它的正确性。     

具有多时间粒度的强全序时态模式中多值依赖问题研究

在时态数据库中存在着与时态多值依赖相关的存储冗余、更新异常等问题.但由于时态多值依赖的复杂性,使得根据时态多值依赖所进行的范式分解并不能总保持无损联接,为此对强全序时态模式中时态多值依赖与无损分解的相关性进行了深入研究,给出了规则的时态多值依赖(RTMVD)和属性集的时间粒度等概念,并给出了RTMVD的一套有效的推理规则,针对强全序时态模式中时态多值依赖与无损分解的相关性给出了相关定理,解决了规则的时态多值依赖环境下时态模式在多粒度上的无损分解问题,为规则时态多值依赖环境下时态模式的进一步规范化奠定了基础.     

具有多时间粒度的时态多值依赖及时态模式分解方法研究

一个好的数据库逻辑设计目标是消除数据冗余以及插入、删除和更新异常.对于时态数据库,通过具有多时间粒度的时态函数依赖约束对时态数据库进行规范化已有大量研究.基于时态函数依赖和多值依赖理论提出了多时间粒度约束的时态多值依赖(TMVD)等概念,并给出了时态多值依赖的推理规则,对其有效性、完备性进行了证明.由于包含有限个TMVD的TMVD集通常蕴含着无限个TMVD,给出了TMVD的有限推理规则,对其有效性、完备性进行了证明.最后,基于时态多值依赖集提出了时态第四范式,并给出了时态模式的T4NF的无损分解算法,对算法的可终止性、正确性进行了证明,并对时间复杂度进行了分析.     

F有弱冲突时产生满足PBC且无α环分解的问题

无环分解是数据库数据组织的一个重要环节,在实际数据库设计中具有重要意义,为了深入研究它,该文分析了在FD集F的最小归并依赖集D存在弱左部或弱右部冲突时所具有的性质和特征,在此基础上讨论了它的模式分解问题,给出了在D有弱冲突时满足无损连接,保FD、BCNF的分解是有α环的结论,为进一步研究无α的分解奠定了基础。     

基于线图的无﹀环混合依赖分解条件及算法

无β环数据库模式具有很多优良的特性 ,以往的研究都局限在图论的范畴内 ,而没有考虑数据库的其他规范化特性 .在混合依赖基概念的基础上 ,定义了严格无冲突、扩展严格无冲突等概念 ,并证明了在混合环境下得出的无损联接、保持依赖、无 β环且满足 4 N F的分解的充要条件是 ,混合依赖集是扩展严格无冲突的 .据此 ,给出了判断严格无冲突及混合环境下无β环分解算法 ,并分析了算法时间的复杂度是线性的 .最后 ,给出基于线图的实例验证 .这一结论可直接指导数据库的模式设计     

基于线图的无β环混合依赖分解条件及算法

无β环数据库模式具有很多优良的特性,以往的研究都局限在图论的范畴内,而没有考虑数据库的其他规范化特性.在混合依赖基概念的基础上,定义了严格无冲突、扩展严格无冲突等概念,并证明了在混合环境下得出的无损联接、保持依赖、无β环且满足4NF的分解的充要条件是,混合依赖集是扩展严格无冲突的.据此,给出了判断严格无冲突及混合环境下无β环分解算法,并分析了算法时间的复杂度是线性的.最后,给出基于线图的实例验证.这一结论可直接指导数据库的模式设计.     

关系模式分解成3NF自动实现

本论文从关系数据库理论中关系模式设计相关问题,讨论了模式分解的重要性,然后根据函数集闭包、属性集闭包求解最小函数依赖集,进而在无损连接和保持函数依赖的前提下,把关系模式分解成3NF。该设计做到了关系模式规范化的自动实现。     

一个多时间粒度下时态模式的T3NF分解算法

对于时态数据库，时间维的引入使得如何有效地进行数据库设计以消除数据冗余和插入、删除异常显得尤为重要．可以通过支持多时间粒度的时态函数依赖（TFDs）约束对时态数模式进行规范化．但是多时间粒度的使用给数据库设计带来巨大的复杂性．一般来说，系统所能处理的和相当多的应用所涉及到的时态类型集满足全序关系．对于这种具有全序时态类型集的时态模式，通过分析TFD臬所具有的良好特性，给出了一个得到满足时态第三范式（T3NF）的无损分解的多项式时间的算法．     

无冲突满足P4的无β环数据库模式 分解条件的研究

无β环是一种重要的无环级别,与无损联接、保持依赖和4NF一起,成为多值依赖环境下数据库模式规范化的基本要求,能够直接指导数据库的模式设计.文中提出了严格无冲突的概念,以线图为工具,证明了应用分解树算法对一个严格无冲突的MVD集分解得到的数据库模式对应的线图及等权化简子图都是三角化的,而且线图中每个三角形都是相容的.最后得出无冲突条件下无β环且满足保持数据依赖、无损联接和4NF 的数据库模式分解的充要条件是给定的MVD集存在一个严格无冲突的覆盖.     

XML DTD的一种范式

研究了XML DTD的规范化问题。由于DTD在设计上存在不足之处，DTD中可能包含类似于关系数据库模式中存在的异常依赖，从而导致XML文档包含冗余的数据和各种操作异常。提出了关于DTD的多值依赖的概念，然后基于多值依赖的概念，提出了一种XML的范式XNF，并且用DTD的关系表示形式给出了关于DTD的无损联接分解的概念。最后给出了把DTD无损联接地分解成XNF的一种算法。     

Approximate dependencies in database systems

Functional dependencies are the most commonly used approach for capturing real-word integrity constraints which are to be reflected in a database. There are, however, many useful kinds of constraints, especially approximate ones, that cannot be represented correctly by functional dependencies and therefore are enforced via programs which update the database, if they are enforced at all. This tends to make such constraints invisible since they are not an explicit part of the database, increasing maintenance problems and the likelihood of inconsistencies. We propose a new approach, cluster dependencies, as a way to enforce approximate dependencies. By treating equality as a fuzzy concept and defining appropriate similarity measures, it is possible to represent a broad range of approximate constraints directly in the database by storing and accessing cluster definitions. We discuss different interpretations of cluster dependencies and describe the additional data structures needed to enforce them. We also contrast them with an existing approach, fuzzy functional dependencies, which are much more limited in the kind of approximate constraints they can represent.     

XML函数依赖研究综述

函数依赖作为数据库规范化的基础在关系理论中起着重要的作用。近年来，XML得到广泛应用并已成为互联网上数据传输和交换的标准。由于XML半结构化的特性，使得如何定义XML函数依赖使其具有更强的描述能力，以及如何解决相应的逻辑蕴涵问题成为当今学术界所面临的挑战。针对这些问题，系统地描述了目前关于XML函数依赖的研究现状，特别是把分析的重点放在如何定义函数依赖、判断其蕴涵关系以及从XML文档中发现函数依赖等问题上。最后讨论了诸如类型化函数依赖关系等一些相关的研究方向。     

Semantic sampling of existing databases through informative Armstrong databases

Functional dependencies (FDs) and inclusion dependencies (INDs) convey most of data semantics in relational databases and are very useful in practice since they generalize keys and foreign keys. Nevertheless, FDs and INDs are often not available, obsolete or lost in real-life databases. Several algorithms have been proposed for mining these dependencies, but the output is always in the same format: a simple list of dependencies, hard to understand for the user. In this paper, we define informative Armstrong databases (IADBs) from databases as being small subsets of an existing database, satisfying exactly the same FDs and INDs. They are an extension of the classical notion of Armstrong databases, but more suitable for the understanding of dependencies, since tuples are real-world tuples. The main result of this paper is to bound the size of an IADB in the case of non-circular INDs. A constructive proof of this result is given, from which an algorithm has been devised. An implementation and experiments against a real-life database were performed; the obtained database contains 0.6% of the initial database tuples only. More importantly, such semantic sampling of databases appear to be a key feature for the understanding of existing databases at the logical level.     

Analysis of dependencies in advanced transaction models

Transactional dependencies play an important role in coordinating and executing the subtransactions in advanced transaction processing models, such as, nested transactions and workflow transactions. Researchers have formalized the notion of transactional dependencies and have shown how various advanced transaction models can be expressed using different kinds of dependencies. Incorrect specification of dependencies can result in unpredictable behavior of the advanced transaction, which, in turn, can lead to unavailability of resources and information integrity problems. In this work, we focus on how to correctly specify dependencies in an advanced transaction. We enumerate the different kinds of dependencies that may be present in an advanced transaction and classify them into two broad categories: event ordering and event enforcement dependencies. Different event ordering and event enforcement dependencies in an advanced transaction often interact in subtle ways resulting in conflicts and redundancies. We describe the different types of conflicts that can arise due to the presence of multiple dependencies and describe how one can detect such conflicts. An advanced transaction may also contain redundant dependencies—these are dependencies that can be logically derived from other dependencies. We show how such extraneous dependencies can be eliminated to get an equivalent set of dependencies that has the same effect as the original set. Our dependency analysis is done in the context of a generalized advanced transaction model that is capable of expressing different kinds of advanced transactions. Recommended by: Amit Sheth     

基于条件函数依赖的数据库一致性检测研究

条件函数依赖是函数依赖在语义上的扩充,可以应用于数据清洗工作,在数据库一致性的修复上应用广泛。讨论了条件函数依赖的相关语义规则,重点研究了基于条件函数依赖对违反数据库一致性元组的检测工作,并引入置信度评价机制,对相关的检测规则进行了改进。改进后的检测方法在基于多个函数依赖的检测中显示出了优越性,使得检测工作更为精简,检测标准更加明确。     

Mining functional dependencies from data

In this paper, we propose an efficient rule discovery algorithm, called FD_Mine, for mining functional dependencies from data. By exploiting Armstrong’s Axioms for functional dependencies, we identify equivalences among attributes, which can be used to reduce both the size of the dataset and the number of functional dependencies to be checked. We first describe four effective pruning rules that reduce the size of the search space. In particular, the number of functional dependencies to be checked is reduced by skipping the search for FDs that are logically implied by already discovered FDs. Then, we present the FD_Mine algorithm, which incorporates the four pruning rules into the mining process. We prove the correctness of FD_Mine, that is, we show that the pruning does not lead to the loss of useful information. We report the results of a series of experiments. These experiments show that the proposed algorithm is effective on 15 UCI datasets and synthetic data.     

Multi-region adaptive finite element-boundary element method for elasto-plastic analysis

In this paper, a multi-region adaptive finite element–boundary element (FEM-BEM) method for elasto-plastic analysis is presented. The method is suitable for several plasticity models, i.e. von-Mises, Tresca, Mohr–Coulomb, Drucker–Prager, Hill, and Hoffman yield criteria. The domain of the original problem is divided into the finite element and the boundary element sub-domains: the FEM is utilized in regions where plastic material behaviour is expected to develop, whereas the complementary linear elastic region is approximated using the symmetric Galerkin BEM. The adaptive method estimates the finite element and boundary element sub-domains, automatically generates the corresponding meshes and adapts the sub-domains, according to the state of computation.     

图依赖研究与应用综述

图依赖是用于解决图数据的数据一致性问题的数据质量规则。基于图依赖提升数据一致性的过程通常分为图依赖定义与形式化、图依赖自动挖掘、基于图依赖的数据一致性提升三步。介绍了针对数据一致性的图依赖理论,并根据拓展类型将图依赖分为基于结构约束拓展、基于语义约束拓展和基于外部约束拓展的图依赖;综述并对比了从图数据中自动挖掘图依赖及其拓展的算法;分析了应用图依赖提高数据一致性的研究现状;总结了当前研究中仍存在的问题,并依据问题展望了图依赖在数据质量领域的应用前景。     

基于成本的MapReduce工作流优化器

对MapReduce栈的不同层进行优化有各自的优缺点。针对MapReduce工作负载的优化问题,提出了相关概念;通过与RoT的对比,介绍了MapReduce工作基于成本的优化及所使用的相关技术,并对MapReduce基于成本的优化进行了评估;基于工作流中的数据流依赖和资源依赖关系,提出了三种工作流优化器,评估了基于成本的工作流优化,并对工作流优化器进行了终端-对-终端的评估;通过实验评估了工作流优化器的优化开销并对这三种工作流优化器的优缺点进行了对比分析。