时态信息处理技术及其应用

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《时态信息处理技术及应用》读者对象为高等院校计算机专业的师生，科研机构及相关领域的研发人员等。时间是自然界无处不在的属性。时态信息处理已经成为现代信息系统的重要组成部分。《时态信息处理技术及应用》系统研究时态信息处理技术及其应用，内容包括：（1）时间模型、时间演算和时态逻辑方法；（2）时态数据库基本概念、时态数据模型、时间算子now的语义和时态数据索引；（3）时态数据查询语言，以TempDB为例介绍时态数据库管理系统的设计和实现；（4）XML、工作流时态扩展和时态知识模型；（5）时态应用模式，并给出一个典型的时态应用实例。

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插图：Abstract Time data is one of the basic data types in database systems. There are two modes of using time data in applications, one is the explicit mode and the other is the implicit mode. In the second mode of application, time attributes of information need to be handled. In this chapter, we introduce three basic types of time data, i.e., point, interval and span. Subsequently, we propose the concepts of temporal information, temporal database and temporal systems, and introduce the basic concepts and core technologies of temporal database. We also analyze the origin and development of temporal information processing technologies and divide the evolution in this research field into three phases. Finally, we analyze the current situation in temporal research field and propose some trends of temporal information technologies.Keywords time data, temporal information, temporal database, temporal system, basic concept, evolution, trends1.1 Application RequirementTime exists everywhere in the world. Its attributes are applied in many areas, such as e-commerce, e-government, global information system, and the stock market. However, some applications process time attribute in the same way as they would process a common attribute. For example, web sites can record logon time of users, but simply regard them as a normal attribute like number or character data type. We call these temporal applications implicit applications. There are other temporal applications that require special time processing mechanisms to manage time attributes. We call these applications explicit applications.

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《时态信息处理技术及应用》由清华大学出版社出版。

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目录

PrefaceList of Figures and TablesPart I Temporal Models and Calculation Methods1 From Time Data to Temporal Information1.1 Application Requirement1.2 What Is Time Data1.2.1 Time Point1.2.2 Time Interval1.2.3 Time Span1.2.4 Complex Time Data1.3 Temporal Information, Temporal Database and Temporal System1.3.1 What Is Temporal Information1.3.2 Temporal Database1.3.3 Temporal System1.4 Origin and Development of Temporal Information Technologies1.4.1 Founding Phase1.4.2 Development Phase1.4.3 Application Phase1.5 Current Situation, Problems and Trends1.5.1 Current Situation1.5.2 Existent Problems in Temporal Database Research1.5.3 TrendsReferences2 Time Calculation and Temporal Logic Method2.1 Time Model2.1.1 Continuous Model2.1.2 Stepwise Model2.1.3 Discrete Model2.1.4 Non Temporal Model2.2 Properties of Time Structure2.2.1 Order Relations of Time Sets2.2.2 First Order Properties of Time Flow2.3 Point-Based Temporal Logic2.3.1 Temporal Extensions Based Snapshot Model2.3.2 Temporal Extensions Based Timestamp Model2.4 Interval-Based Temporal Logic2.4.1 From Interval to Point2.4.2 From Point to Point2.4.3 Temporal Predict2.5 Calculation Based on Span2.6 Other Temporal Calculations in Common Use2.7 Time Granularity and Conversion Calculation2.7.1 Time Granularity and Chronon2.7.2 State of Existence of Time Granularity2.7.3 Operations of Time Granularity2.7.4 Relational Chart of Time Granularity Conversion2.8 Tense Logic2.8.1 Syntax and Semantics of Tense Logic2.8.2 Axiomatics and PropertiesReferences3 Temporal Extension of Relational Algebra3.1 Regular Relational Operations3.1.1 Basic Notions3.1.2 Relational Algebra3.1.3 Relational Calculus3.2 Relational Algebra of Historical Database3.2.1 Basic Notions and Terminologies3.2.2 HRDM Model3.2.3 Historical Relational Algebra of HRDM3.3 Bitemporal Relational Algebra of BCDM3.3.1 Basic Notions and Terminologies3.3.2 Bitemporal Relational Algebra3.4 Snapshot Reducibility and Temporal Completeness3.4.1 Snapshot Reducibility3.4.2 Temporal Semi-Completeness3.4.3 Temporal CompletenessReferencesPart 11 Database Based on Temporal Information4 Temporal Data Model and Temporal Database Systems4.1 Time-Dimensions4.1.1 User-Defined Time4.1.2 Valid Time4.1.3 Transaction Time4.1.4 Two Temporal Variables: Now and UC4.1.5 An Illustration4.2 Temporal Database Types4.2.1 Snapshot Database4.2.2 Historical Database4.2.3 Rollback Database4.2.4 Bitemporal Database4.3 Temporal Data Models4.3.1 Bitemporal Time Stamps4.3.2 BCDM4.3.3 Temporal Entity-Relationship Data Model4.4 Difference from Real-Time DatabaseReferences5 Spatio-Temporal Data Model and Spatio-Temporal Databases5.1 Introduction5.2 Spatio-Temporal Data Model5.2.1 Spatio-Temporal Object5.2.2 Basic Considerations of Spatio-Temporal Modeling5.2.3 Version Based Data Model5.2.4 Event-Based Data Model5.2.5 Constraint-Based Data Model5.2.6 Moving Objects Data Model5.3 Query on Spatio-Temporal Data5.3.1 Spatio-Temporal Data Query5.3.2 Moving Data Query5.3.3 Spatio-Temporal Database Language5.4 Structure of Spatio-Temporal Database System5.4.1 Structure of Complete Type5.4.2 Structure of Layered Type5.4.3 Structure of Extended TypeReference6 Temporal Extension of XML Data Model6.1 Motivation6.1.1 XML Temporal Driven6.1.2 Commercial-Driven Temporal Database6.2 Temporal Research of the Semi-Structured Data6.3 Temporal XML Model and Query MechanismReferences7 Data Operations Based on Temporal Variables7.1 Introduction7.2 Data Model Based on Temporal Variables7.2.1 Order and Temporal Variables7.2.2 Main Body Instances7.2.3 Bitemporal Relation Model Based on Variables7.3 Data Updating7.3.1 Data Inserting7.3.2 Data Deleting7.3.3 Data Modifying7.4 Data Querying7.4.1 Now in Current Versions7.4.2 Now in Non-Current Version7.4.3 Temporal Querying AlgorithmsReferencesPart III Temporal Index Technologies8 Temporal Indexes Supporting Valid Time8.1 Introduction8.2 Summary of Temporal Index8.2.1 Temporal Index Based on Transaction Time8.2.2 Index Based on Valid Time8.2.3 Bitemporal Index8.3 TRdim8.3.1 Relative Temporal Data Model8.3.2 Temporal Relation Index Model8.4 Data Querying and Index Updating8.4.1 Index Querying8.4.2 Index Updating8.5 Simulation8.5.1 Index Constructing8.5.2 Query Based on Probability8.5.3 Query Based on the Number of DataReferences9 Indexes for Moving-Objects Data9.1 Introduction9.2 Data Model for Moving Objects9.2.1 Data Model Modm9.2.2 Temporal Summary9.3 Index for Moving Object Data9.3.1 Linear Order Division……Part IV Temporal Database Management SystemsPart V Temporal Application and Case Study AppendixIndex

封面

书名:时态信息处理技术及其应用

作者:汤庸

页数:未知

定价:¥110.0

出版社:清华大学出版社

出版日期:2010-07-01

ISBN:9787302223900

PDF电子书大小:78MB 高清扫描完整版