声明
Abstract
摘要
Table of Contents
Chapter One Introduction
1.1 Motivation
1.2 Contribution
1.3 State of the Art on Linked Data Query Processing
1.4 Organization
Chapter Two Literature Review and Related Techniques
2.1 The Semantic Web
2.2 Resource Description Framework(RDF)
2.3 SPARQL Protocol and RDF Query Language(SPARQL)
2.4 Ontology Languages
2.4.1 RDF Schema(RDFS)
2.4.2 Web Ontology Language(OWL)
2.5 Linked Data
2.5.1 Linked Open Data
2.5.2 Linked Enterprise Data
2.6 Query Processing
2.7 Information Management
Chapter Three Query Execution Strategies
3.1 Live Query Processing Strategy
3.1.1 Semantic Web Client Library
3.1.2 Linked Data Spider (LDSpider)
3.2 Federated Query Processing
3.3 Index-Based Query Processing
3.4 Hybrid Query Processing
3.5 Link Traversal-Based Query Execution(LTBQE)
Chapter Four Architecture of Query Processing System
4.1 Motivation
4.2 The Model
4.2.1 Query Parsing
4.2.2 Query Analysis
4.2.3 Data Source Selection
4.2.4 Query Execution
4.2.5 Query Results Aggregation
4.3 Apache Jena TDB RDF Data Store
4.4 SQUIN Framework
4.4.1 How SQUIN Works
4.4.2 Linked Data Cache
4.4.3 Link Traversal-Based Query Engine (LTBQE)
4.4.4 Link Traversing
Chapter Five Algorithm Design and Implementation
5.1 Overview of Algorithms
5.2 Seed PopulatorAlgorithm
5.3 Live Query Execution Algorithm for Linked Data
5.4 Implementation Details
5.4.1 Query Parsing
5.4.2 Query Execution
5.4.3 Generating Query Results
Chapter Six Experimentaion and Analysis
6.1 Experimentation Setup
6.1.1 Hardware Setup
6.1.2 Software Setup
6.1.3 Test Dataset
6.1.4 Test Queries
6.2 Research Information Discovery Application
6.2.1 Application Breakdown
6.2.2 User Interfaces
6.2.3 Building a Custom Dataset
6.3 Results and Analysis
Chapter Seven Conclusion and Future Work
7.1 Conclusion
7.2 Future Work
References
Acknowledgements