Home Page Icon
Home Page
Table of Contents for
Dedication
Close
Dedication
by Zachary Ives, Alon Halevy, AnHai Doan
Principles of Data Integration
Cover image
Title page
Table of Contents
Copyright
Dedication
Preface
1. Introduction
1.1 What Is Data Integration?
1.2 Why Is It Hard?
1.3 Data Integration Architectures
1.4 Outline of the Book
Bibliographic Notes
Part I: Foundational Data Integration Techniques
2. Manipulating Query Expressions
2.1 Review of Database Concepts
2.2 Query Unfolding
2.3 Query Containment and Equivalence
2.4 Answering Queries Using Views
Bibliographic Notes
3. Describing Data Sources
3.1 Overview and Desiderata
3.2 Schema Mapping Languages
3.3 Access-Pattern Limitations
3.4 Integrity Constraints on the Mediated Schema
3.5 Answer Completeness
3.6 Data-Level Heterogeneity
Bibliographic Notes
4. String Matching
4.1 Problem Description
4.2 Similarity Measures
4.3 Scaling Up String Matching
Bibliographic Notes
5. Schema Matching and Mapping
5.1 Problem Definition
5.2 Challenges of Schema Matching and Mapping
5.3 Overview of Matching and Mapping Systems
5.4 Matchers
5.5 Combining Match Predictions
5.6 Enforcing Domain Integrity Constraints
5.7 Match Selector
5.8 Reusing Previous Matches
5.9 Many-to-Many Matches
5.10 From Matches to Mappings
Bibliographic Notes
6. General Schema Manipulation Operators
6.1 Model Management Operators
6.2 Merge
6.3 ModelGen
6.4 Invert
6.5 Toward Model Management Systems
6.5 Bibliographic Notes
7. Data Matching
7.1 Problem Definition
7.2 Rule-Based Matching
7.3 Learning-Based Matching
7.4 Matching by Clustering
7.5 Probabilistic Approaches to Data Matching
7.6 Collective Matching
7.7 Scaling Up Data Matching
Bibliographic Notes
8. Query Processing
8.1 Background: DBMS Query Processing
8.2 Background: Distributed Query Processing
8.3 Query Processing for Data Integration
8.4 Generating Initial Query Plans
8.5 Query Execution for Internet Data
8.6 Overview of Adaptive Query Processing
8.7 Event-Driven Adaptivity
8.8 Performance-Driven Adaptivity
Bibliographic Notes
9. Wrappers
9.1 Introduction
9.2 Manual Wrapper Construction
9.3 Learning-Based Wrapper Construction
9.4 Wrapper Learning without Schema
9.5 Interactive Wrapper Construction
Bibliographic Notes
10. Data Warehousing and Caching
10.1 Data Warehousing
10.2 Data Exchange: Declarative Warehousing
10.3 Caching and Partial Materialization
10.4 Direct Analysis of Local, External Data
Bibliographic Notes
Part II: Integration with Extended Data Representations
11. XML
11.1 Data Model
11.2 XML Structural and Schema Definitions
11.3 Query Language
11.4 Query Processing for XML
11.5 Schema Mapping for XML
Bibliographic Notes
12. Ontologies and Knowledge Representation
12.1 Example: Using KR in Data Integration
12.2 Description Logics
12.3 The Semantic Web
Bibliographic Notes
13. Incorporating Uncertainty into Data Integration
13.1 Representing Uncertainty
13.2 Modeling Uncertain Schema Mappings
13.3 Uncertainty and Data Provenance
Bibliographic Notes
14. Data Provenance
14.1 The Two Views of Provenance
14.2 Applications of Data Provenance
14.3 Provenance Semirings
14.4 Storing Provenance
Bibliographic Notes
Part III: Novel Integration Architectures
15. Data Integration on the Web
15.1 What Can We Do with Web Data?
15.2 The Deep Web
15.3 Topical Portals
15.4 Lightweight Combination of Web Data
15.5 Pay-as-You-Go Data Management
Bibliographic Notes
16. Keyword Search
16.1 Keyword Search over Structured Data
16.2 Computing Ranked Results
16.3 Keyword Search for Data Integration
Bibliographic Notes
17. Peer-to-Peer Integration
17.1 Peers and Mappings
17.2 Semantics of Mappings
17.3 Complexity of Query Answering in PDMS
17.4 Query Reformulation Algorithm
17.5 Composing Mappings
17.6 Peer Data Management with Looser Mappings
Bibliographic Notes
18. Integration in Support of Collaboration
18.1 What Makes Collaboration Different
18.2 Processing Corrections and Feedback
18.3 Collaborative Annotation and Presentation
18.4 Dynamic Data: Collaborative Data Sharing
Bibliographic Notes
19. The Future of Data Integration
19.1 Uncertainty, Provenance, and Cleaning
19.2 Crowdsourcing and “Human Computing"
19.3 Building Large-Scale Structured Web Databases
19.4 Lightweight Integration
19.5 Visualizing Integrated Data
19.6 Integrating Social Media
19.7 Cluster- and Cloud-Based Parallel Processing and Caching
Bibliography
Search in book...
Toggle Font Controls
Playlists
Add To
Create new playlist
Name your new playlist
Playlist description (optional)
Cancel
Create playlist
Sign In
Email address
Password
Forgot Password?
Create account
Login
or
Continue with Facebook
Continue with Google
Sign Up
Full Name
Email address
Confirm Email Address
Password
Login
Create account
or
Continue with Facebook
Continue with Google
Prev
Previous Chapter
Copyright
Next
Next Chapter
Preface
We would like to dedicate this book to our students
.
Add Highlight
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click
here
login for view all page.
Day Mode
Cloud Mode
Night Mode
Reset