XML函数依赖研究

为了消除数据冗余,基于关系数据模型的函数依赖理论已经被广泛接受并应用于关系数据库的设计中。XML数据库中同样存在数据冗余。为了设计没有冗余的XML数据库,需要用一种简洁、易于理解的方法来定义XML数据问依赖关系。在无序的结点标记树数据模型上定义了XML子树间的函数依赖,并且给出了一套公理系统用来推导函数依赖,以解决函数依赖的蕴涵问题,最后证明了该公理系统是合理的。     

XML多值依赖的推理规则集问题

XML多值依赖的推理规则集问题是解决XML数据依赖的蕴涵问题的基础,是XML规范化理论的关键问题之一。该文对XML树、树元组等进行了重新定义,与Vincent等人不同,提出了基于DTD的XML多值依赖的概念,通过对XML的关系化表示给出了其形式化定义,定义了XML多值依赖集的闭包、XML多值依赖路径依赖基以及XML多值依赖路径集的闭包等概念,给出了一个有效且完备的推理规则集,并对其有效性及完备性进行了证明。     

基于XML Schema的XML弱函数依赖及其推理规则

为了解决不完全信息环境下可扩展标记语言(XML)弱函数依赖的逻辑蕴涵问题,基于XML Schema研究了XML弱函数依赖及其推理规则。给出了XML Schema、符合XML Schema的不完全XML文档树等概念;基于子树信息等价、子树信息相容的概念提出了XML弱函数依赖的定义和性质;提出了相应的推理规则集,并对其正确性和完备性进行了证明。为不完全信息环境下存在XML弱函数依赖的XML Schema规范化的研究奠定了基础。     

XML上的函数依赖推理

函数依赖是数据语义的重要组成部分,这一概念被引入到XML的领域中.基于DTD,XML的树模型和路径表达式,对节点的值相等和路径节点集作了定义.在此基础上,研究了XML中函数依赖、逻辑蕴涵和路径闭包的概念,证明了函数依赖在给定DTD上的可满足性.提出了一个XML上函数依赖的正确和完备的推理规则集,并给出了一个用于计算路径闭包的算法.     

从DTD映射到关系模式:一种保持数据依赖的映射方法

XML正迅速成为互联网上数据表示和交换的标准．用关系数据库存储XML数据是XML存储策略之一．为了将XML数据存储到关系数据库中，人们研究了从DTD到关系模式的映射方法．提出了一种保持数据依赖的映射方法PDD．与已有的Shared—Inlining方法相比，PDD方法充分考虑了DTD蕴涵的数据依赖关系，保证了XML文档的完整性．通过对泛关系进行模式分解，得到的关系模式保持函数依赖，并且满足2NF．可以证明，这种方法是有效的．     

函数依赖和规范化在关系和XML间的传播

XML和关系的结合是一个重要的研究领域,讨论函数依赖和规范化在关系及XML间的传播问题.首先引入XML上函数依赖和键的定义,并进一步定义XML上的数据冗余和规范化DTD的概念.分别讨论在关系和XML相互转化的过程中,函数依赖的传播问题.针对一种一般化的关系模式DTD表示,证明原有关系中的函数依赖可以在生成的XML文档上得到表示.针对一种常见的XML关系存储方法,说明最终生成关系上的函数依赖与原有XML上函数依赖的对应关系.函数依赖传播的核心意义在于规范化的传播.证明使用上述方法时,若原有的关系是满足BCNF的,则发布得到的DTD也是规范化的;若原始的DTD是规范化的,则得到的关系存储也满足BCNF范式.     

XML DTD规范化处理应用研究

从消除XML DTD文档内数据冗余的角度出发研究了文档的规范化问题，首先引入XML DTD上路径和函数依赖的定义，并提出定义XML上的数据冗余；其次基于函数依赖，提出了规范化的DTD概念和XML DTD规范化处理规则；最后给出了一个将XML DTD转化为规范化的处理算法。     

基于路径表达式的XML第四范式及无冗余性判定

随着XML应用越来越广泛,为避免冗余,XML模式设计也变成了越来越受关注的问题,因此XML规范化理论是一个重要的研究领域.类似于关系数据库,本文从数据库角度出发,以消除数据冗余为目的,研究DTD中以路径表达式为基础的基本定义;因函数依赖和多值依赖是数据语义的重要组成部分,将其引入到XML领域中,形式化定义了XML的函数依赖和多值依赖;基于XML树、函数依赖和多值依赖概念,给出了键、冗余的描述,进而在XML函数依赖和多值依赖并存情况下,提出了满足XML第四范式的条件;给出了满足XML第四范式条件的XML文档树无冗余的判定定理,并通过具体实例及实验证明了XML第四范式的有效性.     

XML强闭包依赖的研究

XML闭包依赖是基本的完整性约束。当XML文档出现不完全信息时,XML闭包依赖同样对于阻止XML数据的更新异常、查询优化以及索引设计具有重要的意义。提出了在不完全信息环境下基于一致路径集合的XML强函数依赖和XML强闭包依赖的定义,研究了XML强闭包依赖的判定定理。在提出XML强闭包依赖推理规则的基础上,对其有效性和完备性进行了证明。最后分析了XML强闭包依赖和XML强函数依赖的关系。     

XML函数依赖的定义及分析

函数依赖是XML数据约束研究的重要组成部分.针对XML中存在的复杂的多种形式的函数依赖约束,分析了数据约束的特点,引入节点值相等的概念,提出了一种DTD的路径语言,进而提出了一种新的XML函数依赖(XFD)的定义,包括相对XFD和绝对XFD.其中,绝对键和相对键是XFD的特例.研究了XFD的逻辑蕴涵与闭包问题,给出一组相应的推理规则,并证明了推理规则的正确性及完备性.     

多时间粒度约束的时态简单范式的分解

数据库逻辑设计的目的是消除数据冗余、插入和删除异常。为使时态模式满足某种范式的要求，要对时态模式进行分解，保持函数依赖和无损连接性是对算法最基本的要求。但对具有多时间粒度的时态模式进行分解时，把TBCNF作为最终目标很难实现保持函数依赖性，把T3NF作为最终目标，又很难达到规范化要求。该文提出了时态简单范式TSNF的概念及相应的分解算法，来弥补以上两点不足。     

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.     

基于函数依赖的模式分解方法

模式分解是关系数据库逻辑设计中的难点，本文基于多年数据库系统设计和教学的经验，提出了基于函数依赖的方便可行的模式分解方法。     

Adding inclusion dependencies to an object-oriented data model with uniqueness constraints

We study an object-oriented data model that allows to express both uniqueness constraints and inclusion dependencies as semantic constraints. The data model is based on a subset of F-logic. Uniqueness constraints comprise path functional dependencies which generalise functional dependencies and reflect the navigational power of object-oriented query languages. As inclusion dependencies, we consider explicit class inclusion constraints, besides inclusions required by class hierarchies, and onto constraints that enforce reachability of objects. For these classes of semantic constraints we present an axiomatisation and prove its inference rules to be correct and complete with respect to general logical implication, leaving the decision problem open. The completeness proof combines the known construction for path functional dependencies alone with a possibly infinite model generation process to enforce onto constraints. The results prepare the grounds for normal forms in object-oriented data models and subsequently for computer aided object-oriented database design, following the decomposition approach for the relational data model. Beyond the application for schema design, the achievements could also be exploited for related tasks like semantic query optimisation and mediated data integration within a variety of graph based data models. Received: 11 October 2000 / 27 January 2003     

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。     

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.     

Inferring dependencies from relations: a conceptual clustering approach

In this paper we consider two related types of data dependencies that can hold in a relation: conjunctive implication rules between attribute‐value pairs, and functional dependencies. We present a conceptual clustering approach that can be used, with some small modifications, for inferring a cover for both types of dependencies. The approach consists of two steps. First, a particular clustered representation of the relation, called concept (or Galois ) lattice , is built. Then, a cover is extracted from the lattice built in the earlier step. Our main emphasis is on the second step. We study the computational complexity of the proposed approach and present an experimental comparison with other methods that confirms its validity. The results of the experiments show that our algorithm for extracting implication rules from concept lattices clearly outperforms an earlier algorithm, and suggest that the overall lattice‐based approach to inferring functional dependencies from relations can be seen as an alternative to traditional methods.     

Functional dependencies among Boolean dependencies

In this paper, we consider functional dependencies among Boolean dependencies (BDs, for short). Armstrong relations are defined for BDs (called BD-Armstrong relations). For BDs, two necessary and sufficient conditions for the existence of BD-Armstrong relations are given. A necessary and sufficient condition for the existence of Armstrong relations for functional dependencies (FDs, for short) is given, which in some sense is more convenient than the condition given in [3]. We give an algorithm that solves the problem of deciding if two BDs imply the same set of functional dependencies. If the BDs are given in perfect disjunctive normal form, then the algorithm requires only polynomial time. Although Mannila and Räihä have shown that for some relations exponential time is needed for computing any cover of the set of FDs defined in this relation, as a consequence, we show that the problem of deciding if two relations satisfy the same set of FDs can be solved in polynomial time. Another consequence is a new correspondence of the families of functional dependencies to the families of Sperner systems. By this correspondence, the estimate of the number of databases given previously in [6] is improved. It is shown that there is a one-to-one correspondence between the closure of the FDs that hold in a BD and its so-calledbasic cover. As applications of basic covers, we obtain a representation of a key, the family of minimal keys and a representation of canonical covers.This research was supported by the Hungarian Foundation for Scientific Research, Grant Nos. OTKA 2575, 2149.