基于关系模型的含空值关系数据库的数据更新

本文以空值的完全语义为基础，以空值环境下基于５值（５ＶＬ）的选择运算为工具，深入研究了基于关于模型的含空值关系数据库的数据更新策略和实现算法     

关系数据库不可用空值的查询与处理

现有的基于关系数据模型的商业数据库采用空值对缺失信息进行建模与处理,然而,单一的空值解释无法体现空值本身的丰富语义。事实上,在相关研究中空值通常被解释为‘值未知’,‘值不可用’以及‘值不存在’等。文中主要研究不可用空值的查询与处理。通过仔细地观察和深刻地理解,分别在传统关系数据库查询和模糊数据库查询中讨论不同语义背景和查询条件下不可用空值的处理和分类。此外,还针对涉及不可用空值的传统关系数据库查询提出选择运算和差运算算法,这些算法使文中的研究更具实用性。     

模糊空值环境下关系数据库的几种数据依赖

介绍了模糊空值环境下的嵌入多值依赖、广义连接依赖、子集依赖,及其相应的公理系统。     

Graph Transformation in Relational Databases

We present a novel approach to implement a graph transformation engine based on standard relational database management systems (RDBMSs). The essence of the approach is to create database views for each rules and to handle pattern matching by inner join operations while negative application conditions by left outer join operations. Furthermore, the model manipulation prescribed by the application of a graph transformation rule is also implemented using elementary data manipulation statements (such as insert, delete, update).     

Mining Short-Rule Covers in Relational Databases

An implication rule Q → R is a statement of the form "for all objects in the database, if an object has the attribute–value pairs Q then it has also the attribute–value pairs R ." This simple type of rule is theoretically interesting, because it supports reasoning, similar to functional dependencies in database theory, and it may be of practical significance because the size of the set of implication rules that hold in a relation can remain substantially high even when mining real data and considering only most general covers; i.e., covers containing rules with unredundant right and left sizes. Motivated by these observations, we focus on the extraction of short-rule covers, which cannot be efficiently mined by standard rule miners. We present an algorithm driven by "negative examples" (i.e., satisfy Q but not R ) to prune the rule-candidate lattice associated with each "positive example" (i.e., satisfies both Q and R ). The algorithm scales up quite well with respect to the number of objects and it is particularly suitable for databases with attributes described by large domains. Furthermore, a perfect hash function ensures extraction of short-rule covers even from databases containing a large number of attributes.     

Multidimensional Index Structures in Relational Databases

Efficient query processing is one of the basic needs for data mining algorithms. Clustering algorithms, association rule mining algorithms and OLAP tools all rely on efficient query processors being able to deal with high-dimensional data. Inside such a query processor, multidimensional index structures are used as a basic technique. As the implementation of such an index structure is a difficult and time-consuming task, we propose a new approach to implement an index structure on top of a commercial relational database system. In particular, we map the index structure to a relational database design and simulate the behavior of the index structure using triggers and stored procedures. This can be easily done for a very large class of multidimensional index structures. To demonstrate the feasibility and efficiency, we implemented an X-tree on top of Oracle8. We ran several experiments on large databases and recorded a performance improvement up to a factor of 11.5 compared to a sequential scan of the database.     

关系数据库中空值的影响与处理

为了实现不完全信息的处理,以关系数据库中空值的完全语义为基础,阐述空值的存在对数据库操作的影响,并给出几种处理空值的方法.对数据库理论研究人员以及数据库程序开发人员有一定的参考作用.     

基于关系数据库的关键词查询

介绍了基于关系数据库的关键词查询问题的研究背景;阐述了解决该问题的两大类方法,即基于数据图的方法和基于模式图的方法,并详细介绍了各种方法的原理以及各自的优缺点;最后展望了未来的研究方向.     

Test-Driven Development of Relational Databases

In test-first development, developers formulate and implement a detailed design iteratively, one test at a time. Test-driven development (also called test-driven design) combines TFD with refactoring, wherein developers make small changes (refactorings) to improve code design without changing the code's semantics. When developers decide to use TDD to implement a new feature, they must first ask whether the current design is the easiest possible design to enable the feature's addition. Implementing test-driven database design involves database refactoring, regression testing, and continuous integration. TDDD is an integrated part of the overall development process, not a standalone activity that data professionals perform in parallel with application TDD. Although from a technical view point, TDDD is relatively straightforward, we must overcome several challenges to its whole sale adoption throughout the IT community     

关系数据库的关键词检索

SQL查询语言被用于检索关系数据库中的数据,但对于没有经验的用户来说,学习复杂的SQL语法是一件困难的事情。实现基于关键词的关系数据库信息检索,将使用户不需要任何SQL语言和底层数据库模式的知识,用搜索引擎的方式来获取数据库中的相关数据。本文总结了基于关键字的数据库检索工作的关键技术和研究进展,展望了今后的研究方向。     

Object-Oriented Databases with Relational DBMSs

The expediency of the use of object-oriented models of data as datalogical models in designing databases is shown, and methods of integration of relational and object-oriented models are considered. A relational scheme for storage of attributes and relations of object-oriented models is proposed.     

关系数据库数字水印技术

随着知识产权保护和信息安全技术的发展,关系数据库数据存在所有权问题,可以采用数字水印技术对其进行数字所有权管理。该文分析了关系数据库中的数据和图像、声频、视频等多媒体数据的区别及关系数据库水印的特点,探讨了几种关系数据库数字水印技术,还分析了对关系数据库数据水印技术的攻击方式和理想的关系数据库水印技术。水印关系数据库对数据库的安全有着广阔前景和实际应用价值。     

XML文档在关系数据库中的规范化存储

提出了一种存储方法，首先把XML文档映射为泛关系模式，再利用算法DeriveFDs推导出XML键所蕴含的泛关系模式上函数依赖集的规范覆盖，根据此规范覆盖，最后将泛关系模式保持函数依赖地分解为3NF模式集。得到了保持XML键约束的规范化存储模式，实现了XML文档在关系数据库中的规范化存储。实验研究表明文中提出的方法是有效的。     

On Normalization of Relations in Relational Databases

A new normal form, namely, object-normal form (ONF), is introduced. It is shown that the existing definitions of the fifth normal form (5NF) are unsatisfactory. The correct definition is given for the first time. The importance of the 5NF is demonstrated. For improving data representation in a database with a 5NF schema, the notion of negating relation is introduced. It serves as a basis for the new normal form, namely, the sixth normal form. Combining requirements of the ONF and other normal forms, new normal forms are defined: the fourth object-normal form, the fifth object-normal form, and the sixth object-normal form. It is shown that the standard order of steps of the normalization procedure should be changed: first, the specific requirements of the fourth normal form should be satisfied, and only then the requirements of the second normal form, and so forth.     

Bottom-Up Association Rule Mining in Relational Databases

Although knowledge discovery from large relational databases has gained popularity and its significance is well recognized, the prohibitive nature of the cost associated with extracting such knowledge, as well as the lack of suitable declarative query language support act as limiting factors. Surprisingly, little or no relational technology has yet been significantly exploited in data mining even though data often reside in relational tables. Consequently, no relational optimization has yet been possible for data mining. We exploit the transitive nature of large item sets and the so called anti-monotonicity property of support thresholds of large item sets to develop a natural least fixpoint operator for set oriented data mining from relational databases. The operator proposed has several advantages including optimization opportunities, and traditional candidate set free large item set generation. We present an SQL3 expression for association rule mining and discuss its mapping to the least fixpoint operator developed in this paper.     

粗关系数据库查询模型

针对粗关系数据库中数据的特性,提出一种不确定性数据的存储方法。基于汉明距离的一种变式,计算元组间距离,构成距离矩阵,根据距离矩阵将相同或相近的元组归类,从而有效地对表中的元组进行索引。借助粗集中的上、下近似,通过计算用户查询的数据与粗关系数据库中数据的相似度,查询出用户所需的数据。结合以上方法构建粗关系数据库查询模型,设计相应的查询算法并应用于实例中。     

Table Oriented Metrics for Relational Databases

Developing and selecting high quality software applications are fundamental. It is important that the software applications can be evaluated for every relevant quality characteristic using validated metrics. Software engineers have been putting forward hundreds of quality metrics for software programs, disregarding databases. However, software data aspects are important because the size of data and their system nature contribute to many aspects of a systems quality. In this paper, we proposed some internal metrics to measure relational databases which influence its complexity. Considering the main characteristics of a relational table, we can propose the number of attributes (NA) of a table, the depth of the referential tree (DRT) of a table, and the referential degree (RD) of a table. These measures are characterized using measurement theory, particularly the formal framework proposed by Zuse. As many important issues faced by the software engineering community can only be addressed by experimentation, an experiment has been carried out in order to validate these metrics.     

Watermarking Relational Databases Using Optimization-Based Techniques

Proving ownership rights on outsourced relational databases is a crucial issue in today's internet-based application environments and in many content distribution applications. In this paper, we present a mechanism for proof of ownership based on the secure embedding of a robust imperceptible watermark in relational data. We formulate the watermarking of relational databases as a constrained optimization problem and discuss efficient techniques to solve the optimization problem and to handle the constraints. Our watermarking technique is resilient to watermark synchronization errors because it uses a partitioning approach that does not require marker tuples. Our approach overcomes a major weakness in previously proposed watermarking techniques. Watermark decoding is based on a threshold-based technique characterized by an optimal threshold that minimizes the probability of decoding errors. We implemented a proof of concept implementation of our watermarking technique and showed by experimental results that our technique is resilient to tuple deletion, alteration, and insertion attacks.