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實用語義網(wǎng):RDFS與OWL高效建模(英文版)

實用語義網(wǎng):RDFS與OWL高效建模(英文版)

定 價:¥59.00

作 者: (美)阿利芒,(美)亨德勒 著
出版社: 人民郵電出版社
叢編項: 圖靈原版計算機科學系列
標 簽: 人工智能

ISBN: 9787115193841 出版時間: 2009-02-01 包裝: 平裝
開本: 16開 頁數(shù): 330 字數(shù):  

內(nèi)容簡介

  語義網(wǎng)的發(fā)展孕育著萬維網(wǎng)及其應用的一場革命,作為語義網(wǎng)核心內(nèi)容的語言——RDF和OWL,逐漸得到廣泛的重視和應用。本書是語義網(wǎng)的入門教程,詳細講述語義網(wǎng)的核心內(nèi)容的語言,包括語義網(wǎng)的概念、語義建模、RDF、RDF Schema、OWL基礎(chǔ)等。本書對于任何對語義網(wǎng)感興趣的專業(yè)技術(shù)人員都是十分難得的參考書。

作者簡介

  Dean Allemang,世界知名的語義網(wǎng)專家。英國劍橋大學數(shù)學專業(yè)碩士,美國俄亥俄州立大學計算機專業(yè)博士。有豐富的語義網(wǎng)開發(fā)經(jīng)驗,曾創(chuàng)辦了最早的一家語義網(wǎng)技術(shù)公司,目前擔任美國領(lǐng)先的語義網(wǎng)技術(shù)公司TopQLladrant的首席科學家。JoumalofWebSemantics編委。世界最大的語義網(wǎng)研究機構(gòu)DigitalEnterprise研究院的評審委員會成員。自2003年起一直擔任國際語義網(wǎng)會議工業(yè)應用方向的主席。James Hendler,語義網(wǎng)的創(chuàng)始人之一,萬維網(wǎng)聯(lián)盟語義網(wǎng)協(xié)調(diào)組成員。美國人工智能協(xié)會和英國計算機協(xié)會會士。曾任美國國防部高級研究計劃局(DARPA)的信息系統(tǒng)辦公室首席科學家。目前是Rensselaer理工學院教授,并兼任麻省理工學院Web科學研究項目的副主任。他還是IEEEIntelligentSystems的主編,也是第一位擔任美國《科學》雜志評審委員的計算機科學家。

圖書目錄

CHAPTER 1 What Is the Semantic Web?
What Is a Web?
Smart Web, Dumb Web
Smart Web Applications
A Connected Web Is a Smarter Web
Semantic Data
A Distributed Web of Data
Features of a Semantic Web
What about the Round-Worlders?
To Each Their Own
There's Always One More
Summary
Fundamental Concepts
CHAPTER 2 Semantic Modeling
Modeling for Human Communication
Explanation and Prediction
Mediating Variability
Variation and Classes
Variation and Layers
Expressivity in Modeling
Summary
Fundamental Concepts
CHAPTER 3 RDF--The Basis of the Semantic Web
Distributing Data Across the Web
Merging Data from Multiple Sources
Namespaces, URIs, and Identity
Expressing URIs in Print
Standard Namespaces
Identifiers in the RDF Namespace
Challenge- RDF and Tabular Data
Higher-Order Relationships
Alternatives for Serialization
N-Triples
Notation 3 RDF (N3)
RDF/XML
Blank Nodes
Ordered Information in RDF
Summary
Fundamental Concepts
CHAPTER 4 Semantic Web Application Architecture
RDF Parser/Serializer
Other Data Sources--Converters and Scrapers
RDF Store
RDF Data Standards and Interoperability of
RDF Stores
RDF Query Engines and SPARQL
Comparison to Relational Queries
Application Code
RDF-Backed Web Portals
Data Federation
Summary
Fundamental Concepts
CHAPTER 5 RDF and Inferencing
Inference in the Semantic Web
Virtues of hfference-Based Semantics
Where are the Smarts?
Asserted Triples versus Inferred Triples
When Does Inferencing Happen?
Inferencing as Glue
Summary
Fundamental Concepts
CHAPTER 6 RDF Schema
Schema Languages and Their Functions
What Does It Mean? Semantics as Inference
The RDF Schema Language
Relationship Propagation through
rdfs:subPropertyOf
Typing Data by Usage--rdfs:domain
and rdfs:range
Combination of Domain and Range with
rdfs:subClassOf
RDFS Modeling Combinations and Patterns
Set Intersection
Property Intersection
Set Union
Property Union
Property Transfer
Challenges
Term Reconciliation
Instance-Level Data Integration
Readable Labels with rdfs:label
Data Typing Based on Use
Filtering Undefined Data
RDFS and Knowledge Discovery
Modeling with Domains and Ranges
Multiple Domains/Ranges
Nonmodeling Properties in RDFS
Cross-Referencing Files: rdfs:seeAlso
Organizing Vocabularies: rdfs:isDefmedBy
Model Documentation: rdfs:comment
Summary
Fundamental Concepts
CHAPTER RDFS-Plus
Inverse
Challenge: Integrating Data that Do Not Want
to Be Integrated
Challenge: Using the Modeling Language to
Extend the Modeling Language
Challenge: The Marriage of Shakespeare
Symmetric Properties
Using OWL to Extend OWL
Transitivity
Challenge: Relating Parents to Ancestors
Challenge: Layers of Relationships
Managing Networks of Dependencies
Equivalence
Equivalent Classes
Equivalent Properties
Same Individuals
Challenge: Merging Data from Different Databases
Computing Sameness--Functional Properties
Functional Properties
Inverse Functional Properties
Combining Functional and Inverse
Functional Properties
A Few More Constructs
Summary
Fundamental Concepts
CHAPTER 8 Using RDFS-Plus in the Wild
SKOS
Semantic Relations in SKOS
Meaning of Semantic Relations
Special Purpose Inference
Published Subject Indicators
SKOS in Action
FOAF
People and Agents
Names in FOAF
Nicknames and Online Namds
Online Persona
Groups of People
Things People Make and Do
Identity in FOAF
It's Not What You Know, It's Who You Know
Summary
Fundamental Concepts
CHAPTER 9 Basic OWL
Restrictions
Example: Questions and Answers
Adding "Restrictions"
Kinds of Restrictions
Challenge Problems
Challenge: Local Restriction of Ranges
Challenge: Filtering Data Based on Explicit Type
Challenge: Relationship Transfer in SKOS
Relationship Transfer in FOAF
Alternative Descriptions of Restrictions
Summary
Fundamental Concepts
CHAPTER 10 Counting and Sets in OWL
Unions and Intersections
Closing the World
Enumerating Sets with owL'oneOf
Differentiating Individuals with
owl:differentFrom
Differentiating Multiple Individuals
Cardinality
Small Cardinality Limits
Set Complement
Disjoint Sets
Prerequisites Revisited
No Prerequisites
Counting Prerequisites
Guarantees of Existence
Contradictions
Unsatisfiable Classes
Propagation of Unsatisfiable Classes
Inferring Class Relationships
Reasoning with Individuals and with Classes
Summary
Fundamental Concepts
CHAPTER 11 Using OWL in the Wild
The Federal Enterprise Architecture Reference
Model Ontology
Reference Models and Composability
Resolving Ambiguity in the Model: Sets
versus Individuals
Constraints between Models
OWL and Composition
owl:Ontology
owl:imports
Advantages of the Modeling Approach
The National Cancer Institute Ontology
Requirements of the NCI Ontology
Upper-Level Classes
Describing Classes in the NCI Ontology
Instance-Level Inferencing in the NCI Ontology
Summary
Fundamental Concepts
CHAPTER 12 Good and Bad Modeling Practices
Getting Started
Know What You Want
Inference Is Key
Modeling for Reuse
Insightful Names versus Wishful Names
Keeping Track of Classes and Individuals
Model Testing
Common Modeling Errors
Rampant Classism (Antipattern)
Exclusivity (Antipattern)
Objectification (Antipattern)
Managing Identifiers for Classes (Antipattern)
Creeping Conceptualization (Antipattern)
Summary
Fundamental Concepts
CHAPTER 13 OWL Levels and Logic
OWL Dialects and Modeling Philosophy
Provable Models
Executable Models
OWL Full versus OWL DL
Class/Individual Separation
InverseFunctional Datatypes
OWL Lite
Other Subsets of OWL
Beyond OWL 1.0
Metamodeling
Multipart Properties
Qualified Cardinality
Multiple Inverse Functional Properties
Rules
Summary
Fundamental Concepts
CHAPTER 14 Conclusions
APPENDIX Frequently Asked Questions
Further Reading
Index

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