含有效时间时态关系数据库到XML映射方法的研究

在讨论现有时态XML数据模型的基础上,引入有效时间XML表示模型,进而研究含有效时间时态关系数据库到时态XML文档的映射问题.给出时态关系数据库到时态XML文档映射的一般性映射规则,重点研究时态关系数据库中一些复杂映射问题,包括类层次、联系集、弱实体集的映射转换问题.     

基于时态变量对象关系模型及代数运算

时态数据处理多是基于关系数据库平台,时态数据库模型也以时态关系数据模型为主.关系数据模型难以处理具有复杂类型的数据对象,而面向对象数据模型还缺乏商业化应用平台.现有关系数据库平台大多增加了面向对象基本功能,形成了对象关系数据库系统,因此将对象关系数据模型进行时态扩充就显得十分必要和具有可行性.首先在现有时态关系数据模型基础上,提出了一种基于对象关系双时态数据模型,而这种数据模型适合于在现有数据库平台上实现;其次,在该模型框架内,讨论了时态对象关系模式与时态关系模式相互间的联系与转换,这也是由时态关系扩充到对象关系的基本要求;再次,分析了时态模型中时态变量复杂语义和相应绑定算法,这是时态数据库能够有效运行的基本课题之一;最后,研究了基于时态变量复杂语义的时态对象关系数据操作代数,从而为时态对象关系模式的查询进行了必要的理论探讨.     

一种基于时态的扩展值辩论框架

时间是用来描述辩论过程以及辩论活动变化的一个重要因素,在辩论框架中加入时间因素是积极的。本文结合Dung的标准辩论框架以及Bench-Capon的基于值的辩论框架,提出了基于时态的扩展值辩论框架。首先分析了Dung的辩论框架以及Bench-Capon的值辩论框架在时态以及辩论值方面描述的局限性及需求,然后结合这些需求提出了基于时态的扩展值辩论框架,给出了完整的框架结构和语义描述,证明了基于时态的扩展值辩论框架满足Dung提出的标准辩论框架的一些基本定理。     

时态数据库在工资智能决策支持系统的应用

本文针对工资智能决策支持系统的时态性进行了讨论，并用一个基于时态数据库的嵌套关系数据库及其TER模型实现。     

时态外推推理诊断模型

本文通过引入时态一致覆盖集的概念,提出一个基于时态推理与覆盖技术的时态外推推理诊断模型TGSC.TGSC利用模糊集描述有关征兆、故障及相互间关系的时态知识,文中建立了TGSC的基本框架,给出了基于假设图搜索的诊断问题的求解方法,并给出计算示例。     

时态面向对象数据库查询算法研究

时态关系数据库在关系数据库的基础上扩充了对时间数据的处理、而时态面向对象数据库则是在面向对象数据库的基础上扩充了对时间数据的处理。在时态数据基态修正模型的基础上,讨论了时态面向对象数据库查询优化策略,并给出相应的算法。     

时态覆盖集诊断模型TGSC

本文通过引入时态一致覆盖集的概念，提出了一个基于时态推理与覆盖技术的时态覆盖集诊断模型ＴＧＳＣ。ＴＧＳＣ利用模糊描述有关征兆、故障及相互间关系的时态知识。文中建立了ＴＧＳＣ的基本框架。给出了基于假设图搜索的诊断问题求解方法，并伴以计算示例。     

房产信息系统中的时空数据管理

在图形、属性一体化存储的面向对象全关系数据库模型的基础上，就房产信息系统中的时态问题给出了一个基于房产实体对象周期的时空数据管理方法，并扼要论述了基于时态功能的实现算法。     

基于关系数据库实现时态数据库

事物随时间变化的特性广泛存在,在其属性的特征值上存在着大量时态数据。然而关系数据库由于关系模型本身限制,基于关系的时态信息处理难以有效表示时态对象复杂的数据结构,不具备直接的时态数据管理能力。以简易的人事信息管理系统为例,对基于关系数据库的时态数据存取进行了探讨。     

基数为M的时态候选关键字问题研究

为了更有效地研究时态数据库中各种时态依赖以及各属性之间的关系,对时态候选关键字的求解进行了研究,定义了时态准左部属性、时态准右部属性和时态纯双部属性等概念;结合关系数据库理论给出了时态最大相关块法求时态候选关键字,并对相关理论进行了证明,这对实现时态候选关键字的规范化问题具有重要的推动作用.     

Qualitative and quantitative temporal constraints and relationaldatabases: theory, architecture, and applications

Many different applications in different areas need to deal with both: databases, in order to take into account large amounts of structured data; and quantitative and qualitative temporal constraints about such data. We propose an approach that extends: temporal databases and artificial intelligence temporal reasoning techniques and integrate them in order to face such a need. Regarding temporal reasoning, we consider some results that we proved recently about efficient query answering in the Simple Temporal Problem framework and we extend them in order to deal with partitioned sets of constraints and to support relational database operations. Regarding databases, we extend the relational model in order to consider also qualitative and quantitative temporal constraints both in the data (data expressiveness) and in the queries (query expressiveness). We then propose a modular architecture integrating a relational database with a temporal reasoner. We also consider classes of applications that fit into our approach and consider patient management in a hospital as an example     

时态类型集的封闭集

好的数据库逻辑设计目标是消除数据冗余以及插入和删除异常。对于时态数据库，可以利用具有多时间粒度的时态函数依赖（TFDs）约束对时态数据库进行规范化。要进行有效的数据库设计，需要解决有限属性闭包和成员籍等一些有关TFD的问题。为了方便计算机对时态类型的处理和找到有效的解决TFD的相关问题的算法，该文提出了封闭时态类型集的概念，并且给出了一个求给定TFD集的封闭集的算法。     

Querying Temporal Constraint Networks: A Unifying Approach

We develop the scheme of indefinite constraint databases using first-order logic as our representation language. When this scheme is instantiated with temporal constraints, the resulting formalism is more expressive than standard temporal constraint networks. The extra representational power allows us to express temporal knowledge and queries that have been impossible to express before. To make our claim more persuasive, we survey previous works on querying temporal constraint networks and show that they can be viewed as an instance of the scheme of indefinite constraint databases.     

Extending existing dependency theory to temporal databases

Normal forms play a central role in the design of relational databases. Several normal forms for temporal relational databases have been proposed. These definitions are particular to specific temporal data models, which are numerous and incompatible. The paper attempts to rectify this situation. We define a consistent framework of temporal equivalents of the important conventional database design concepts: functional dependencies, primary keys, and third and Boyce-Codd normal forms. This framework is enabled by making a clear distinction between the logical concept of a temporal relation and its physical representation. As a result, the role played by temporal normal forms during temporal database design closely parallels that of normal forms during conventional database design. These new normal forms apply equally well to all temporal data models that have timeslice operators, including those employing tuple timestamping, backlogs, and attribute value timestamping. As a basis for our research, we conduct a thorough examination of existing proposals for temporal dependencies, keys, and normal forms. To demonstrate the generality of our approach, we outline how normal forms and dependency theory can also be applied to spatial and spatiotemporal databases     

Reconciling point-based and interval-based semantics in temporal relational databases: a treatment of the Telic/Atelic distinction

The analysis of the semantics of temporal data and queries plays a central role in the area of temporal databases. Although many different algebrae and models have been proposed, almost all of them are based on a point-based (snapshot) semantics for data. On the other hand, in the areas of linguistics, philosophy, and recently, artificial intelligence, an oft-debated issue concerns the use of an interval-based versus a point-based semantics. In this paper, we first show some problems inherent in the adoption of a point-based semantics for data, then argue that these problems arise because there is no distinction drawn in the data between telic and atelic facts. We then introduce a three-sorted temporal model and algebra including coercion functions for transforming relations of one sort into relations of the other at query time which properly copes with these issues.     

The Design and Evaluation of a Magnetic/Optical Access Structure for Temporal Databases

This paper describes a magnetic/optical access structure for append–only temporal databases. We formally define the properties of an access structure, called the MonotonicB ⁺ -Tree (MBT), that is well suited for Write-Once Read Many optical disks. We present an insertion algorithm for the MBT that does not require splitting of index nodes and give the time analysis for this algorithm. We also describe a storage architecture where optical disks work in tandem with magnetic disks. Magnetic disks are used for storing current versions and recent past versions, whereas optical disks are dedicated for archiving older past versions. Our archiving techniques: (1) allow temporal data and the MBT access structure to span magnetic disks and optical disks; (2) minimize the overhead of the migration process by taking advantage of append–only nature of temporal databases; (3) gracefully handle object versions with very long time intervals so that the delay in the migration process is kept to minimum; and (4) ensure that no false magnetic or optical disk address lookup is performed during search operations by duplicating some closed versions on both magnetic and optical disks. To validate our claims for the efficiency of migration techniques, we analyze the performance of temporal access structures partitioned between magnetic and optical disks. We show that the migration process has a minimal effect on the search time. Our simulation identifies important parameters, and shows how they affect the performance of the temporal access structures. These include mean of version lifespan, block size, query time interval length, and total number of versions.     

Constraint-based Interoperability of Spatiotemporal Databases*

We propose constraint databases as an intermediate level facilitating the interoperability of spatiotemporal data models. Constraint query languages are used to express translations between different data models. We illustrate our approach in the context of a number of temporal, spatial, and spatiotemporal data models.     

Constraint graph-based frequent pattern updating from temporal databases

There have been many kinds of association rule mining (ARM) algorithms, e.g., Apriori and FP-tree, to discover meaningful frequent patterns from a large dataset. Particularly, it is more difficult for such ARM algorithms to be applied for temporal databases which are continuously changing over time. Such algorithms are generally based on repeating time-consuming tasks, e.g., scanning databases. To deal with this problem, in this paper, we propose a constraint graph-based method for maintaining frequent patterns (FP) discovered from the temporal databases. Particularly, the constraint graph, which is represented as a set of constraint between two items, can be established by temporal persistency of the patterns. It means that some patterns can be used to build the constraint graph, when the patterns have been shown in a set of the FP. Two types of constraints can be generated by users and adaptation. Based on our scheme, we find that a large number of dataset has been efficiently reduced during mining process and the gathering information while updating.     

生物化学分子数据库分析和设计研究

讨论了在新药物发现与设计中化学分子数据库的设计和应用这一较新的应用领域,通过对分子数据库结构和特征的分析,提出了一种可行的数据库的设计模型,分析了模型中的各个模块的结构和功能,讨论了数据冗余的处理和数据库的管理,并提出了一些有待解决的问题。