时态数据的变粒度分段存储策略及其效益分析

根据时态数据库用户对数据厚今薄古的需求特点,该文提出变粒度分段存储技术,将一个对象的历史分为3个时期,分介质、变粒度存储.文章讨论了分段存储的特殊数据结构、时代转移算法和压缩采样算法.基于微机实用参数的定量分析表明,这一技术将时态存储密度和时态查询速度提高了一个数量级.     

时态RDF数据存储策略研究

我们的生活中几乎所有的事物都或多或少的具有时态特征，时态数据的处理已经成为当前重要的研究热点之一。时态信息处理在电子商务、数据挖掘、信息提取、电力系统、医疗系统、时空和多媒体信息技术以及网络应用等方面发挥着越来越重要的作用。另一方面，为了提高互联网的智能程度，语义网的不断发展。资源描述框架（RDF）作为语义网实现的基础，因此大量时态RDF格式的数据涌入网络。截止到目前为止，并没有针对时态RDF数据的有效存储方案。在原有时态RDF模型的基础之上， 分析了传统RDF存储方式在时态RDF数据存储上的可行性并提出了一种新的存储方案。     

基于时态数据的CSCL系统设计与实现的探讨

CSCL(计算机支持协同学习)是利用计算机技术、网络技术和远程通信技术来实现整个教与学的过程。随着时间的积累,数据库中会保存着大量的信息,这些信息包括过去、将来和现在的,并且是同等重要的。传统数据库很难体现这些数据的时态性,数据处理的时空效率受到局限。时态数据库是指能够处理时间信息的数据库,存放对象的现状以及过去的一切状态,并且可以根据对象现在和过去的状态推测其未来可能的状态。因此,该文讲述如何实现用户兴趣的分段存储、用户稳定兴趣的获取并降低用户数据存储量。     

时态数据库中二维数据的合并

在时态数据库中,通过不同方式对某一事物监控,获取到的信息可能会有冗余。本文定义了一种时态数据模型,然后在此时态数据模型的基础上,提出了一种消除时态数据冗余的合并算法。通过该算法,我们可以将得到的数据高效、迅速地进行整合,从而达到消除冗余数据的目的。最后,我们还分析了本算法的时间复杂度及其适用范围。     

时态数据的一种挖掘算法

时态数据挖掘是数据挖掘中一个日益重要的研究课题。本文针对时态数据中的多维关系模型，提出了一种新的时态数据建模算法。     

数据的时态性及其在非时态DBMS上的处理

基于数据的时态性和传统的DBMS的局限,结合现代学者对时态数据库的研究成果,提出在非时态DBMS中的处理时态数据的几个实用方法,希望能对具体的时态数据处理和时态数据库的研究带来帮助。     

多时间粒度下时态数据库设计中时态类型的处理

在许多大型信息系统中需要存储大量的历史数据．为了有效地组织这些时间变化数据，可以使用时态函数依赖（TFDs）对时态数据库进行有效地设计．由于多时间粒度的使用，数据库设计算法需要在计算机上实现表示时态类型间的关系的逻辑结构和时态类型间的相关操作．为此提出了细于关系矩阵和封闭的时态类型集，并且对于给定的时态类型集及其细于关系矩阵，给出了一个自动生成它的一个封闭集及封闭集对应的细于关系矩阵的有效算法，通过提出的细于关系矩阵和封闭集算法，可以方便地在计算机上实现时态数据库设计算法需要的时态类型间的细于关系比较和glb操作。     

时态多媒体数据的生长过程及其处理算法

在处理历史性事件伴随的多媒体信息时，一大类带有时态语义的信息可归结为生长过程进行处理，本文给出了生长过程的数学模型，讨论了生长过程的可加性、单调性和简单生长过程的稳定性，介绍了在时态多媒体数据库管理系统原型ＭＨＢａｓｅ中处理生长过程的放弃平凡算法和非平凡增量算法的实现技术。     

多维数据模型的变粒度存储策略研究

提高联机分析处理(OLAP)的响应速度是数据仓库研究的核心问题之一。文中根据多维数据模型的结构特点以及OLAP需求提出了一种变粒度存储策略。实验表明该策略能有效地减少存储空间，提高OLAP响应速度。     

基于Hadoop的时态信息存储与时态关系演算问题研究

面对海量的非结构化时态信息,构建了在分布式环境下的数据存储模型,并在此基础上提出一种基本的时态数据处理方法。使用Hadoop平台下的分布式、非结构化数据库HBase对海量时态数据进行存储,构造以时态集合为时态存储单元的时态数据存储模型;针对分布式处理特征和时态集合数据类型,提出一种在Map/Reduce编程计算模式下进行海量时态信息关系演算的实现方法;通过扩展时态区间关系运算,实现以时态集合为基本时态数据操作对象的交、并等关系运算。以医疗时态数据作为研究实例,表明了所提出的时态数据存储模型和关系演算方案在分布式应用系统下的适用性。     

Hypothetical Temporal Reasoning in Databases

In this paper we integrate a history–encoding based methodology for checking dynamic database integrity constraints into a situation-calculus based specification of relational database updates. By doing this, we are able to: (1) Answer queries about a whole hypothetical evolution of a database, without having to update the entire database and keep all the information associated to the generated states, (2) State and prove dynamic integrity constraints as static integrity constraints, (3). Transform history dependent preconditions for updates into local preconditions.The methodology presented here is based on the introduction of operators of predicate past temporal logic as macros into the specifications, written in the situation calculus, of the dynamics of a database. Temporal subformulas of a query are treated as auxiliary views with the corresponding specification of their dynamics. An implementation of hypothetical temporal query answering is presented.     

Schema Vacuuming in Temporal Databases

Temporal databases facilitate the support of historical information by providing functions for indicating the intervals during which a tuple was applicable (along one or more temporal dimensions). Because data are never deleted, only superceded, temporal databases are inherently append-only resulting, over time, in a large historical sequence of database states. Data vacuuming in temporal databases allows for this sequence to be shortened by strategically, and irrevocably, deleting obsolete data. Schema versioning allows users to maintain a history of database schemata without compromising the semantics of the data or the ability to view data through historical schemata. While the techniques required for data vacuuming in temporal databases have been relatively well covered, the associated area of vacuuming schemata has received less attention. This paper discusses this issue and proposes a mechanism that fits well with existing methods for data vacuuming and schema versioning.     

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.     

Handling of Alternatives and Events in Temporal Databases

Planning for the future is an important activity both at the individual and organizational levels. Planning consists of defining alternative actions to handle various events in the future. The alternatives arise becau]se of different possible outcomes of events. A plan consists of a sequence of actions to be carried out for each possible outcome. In the context of database modeling, the actions are operations on a database. A database management system should enable its users to define events and alternatives, and also allow them to interact with the database under different alternatives (possibly to evaluate different plans). The existing temporal data models treat the future analogous to the past or present; they provide for one future path (in the sense that facts valid at some future time can be stored), but do not provide support for alternatives in the future. In this paper, we present a model for incorporating events and alternatives by extending the temporal data model to support branching time. The extended model permits definitions of events, their interdependencies and associated actions. The events that affect an object are modeled by a tree, permitting an object to have different states at the same valid time but under different alternatives. The branching time paradigm is obtained by superimposing a linear valid time on the event tree. We extend the temporal relational algebra and the Temporal SQL2 to support a branching time data model. The paper also briefly deals with the uncertainties associated with future planning as well as probabilities of possible event outcomes. Finally, we sketch an implementation strategy for the branching time data model.     

Temporal Coupling Verification in Time Series Databases

Time series are often generated by continuous sampling or measurement of natural or social phenomena. In many cases, events cannot be represented by individual records, but instead must be represented by time series segments (temporal intervals). A consequence of this segment-based approach is that the analysis of events is reduced to analysis of occurrences of time series patterns that match segments representing the events.A major obstacle on the path toward event analysis is the lack of query languages for expressing interesting time series patterns. We have introduced SQL/LPP (Perng and Parker, 1999). Which provides fairly strong expressive power for time series pattern queries, and are now able to attack the problem of specifying queries that analyze temporal coupling, i.e., temporal relationships obeyed by occurrences of two or more patterns.In this paper, we propose SQL/LPP+, a temporal coupling verification language for time series databases. Based on the pattern definition language of SQL/LPP (Perng and Parker, 1999), SQL/LPP+ enables users to specify a query that looks for occurrences of a cascade of multiple patterns using one or more of Allen's temporal relationships (Allen, 1983) and obtain desired aggregates or meta-aggregates of the composition. Issues of pattern composition control are also discussed.     

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。