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Query processing over uncertain databases
Author
Title
Query processing over uncertain databases [electronic resource] / Lei Chen, Xiang Lian.
ISBN
9781608458936 (electronic bk.)
9781608458929 (pbk.)
Published
San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, c2013.
Physical Description
1 online resource (x, 91 p.) : ill., digital file.
Local Notes
Access is available to the Yale community.
Notes
Part of: Synthesis digital library of engineering and computer science.
Series from website.
Title from PDF t.p. (viewed on January 18, 2013).
Access and use
Access restricted by licensing agreement.
Summary
Due to measurement errors, transmission lost, or injected noise for privacy protection, uncertainty exists in the data of many real applications. However, query processing techniques for deterministic data cannot be directly applied to uncertain data because they do not have mechanisms to handle the data uncertainty. Therefore, efficient and effective manipulation of uncertain data is a practical yet challenging research topic. In this book, we start from the data models for imprecise and uncertain data, move on to defining different semantics for queries on uncertain data, and finally discuss the advanced query processing techniques for various probabilistic queries in uncertain databases.The book serves as a comprehensive guideline for query processing over uncertain databases.
Other formats
Also available in print.
Print version:
Format
Books / Online
Language
English
Added to Catalog
April 24, 2013
Series
Synthesis lectures on data management, # 33
System details note
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
Bibliography
Includes bibliographical references (p. 83-89).
Contents
1. Introduction
1.1 Uncertain data management
1.2 Real applications of uncertain data management
1.3 Classifications of uncertain data
1.4 Major challenges of uncertain data management
1.5 Outline
2. Uncertain data models
2.1 Uncertain databases
2.2 Possible worlds semantics
2.3 Independent uncertainty model
2.4 Correlated uncertainty model
2.5 Uncertainty model with local correlations
2.6 Exercises
3. Spatial query semantics over uncertain data models
3.1 A warm-up example of probabilistic range query
3.2 Probabilistic nearest neighbor queries
3.2.1 Motivation
3.2.2 Background
3.2.3 Definition of PNN
3.3 Probabilistic reverse nearest neighbor queries
3.3.1 Motivation
3.3.2 Background
3.3.3 Definition of PRNN
3.4 Probabilistic reverse skyline queries
3.4.1 Motivation
3.4.2 Definition of PRS
3.5 Exercises
4. Spatial query processing over uncertain databases
4.1 General framework
4.1.1 The filter-and-refine framework
4.1.2 Highlights of basic pruning techniques
4.2 Spatial pruning
4.2.1 Spatial pruning for probabilistic nearest neighbor queries
4.2.2 Spatial pruning for probabilistic reverse nearest neighbor queries
4.2.3 Spatial pruning for probabilistic reverse skyline queries
4.3 Probabilistic pruning
4.3.1 Probabilistic pruning for probabilistic nearest neighbor queries
4.3.2 Probabilistic pruning for probabilistic reverse nearest neighbor queries
4.3.3 Probabilistic pruning for probabilistic reverse skyline queries
4.4 Refinement
4.4.1 Refinement for probabilistic nearest neighbor queries
4.4.2 Refinement for probabilistic reverse nearest neighbor queries
4.4.3 Refinement for probabilistic reverse skyline queries
4.5 Query procedure
4.5.1 Probabilistic nearest neighbor query answering
4.5.2 Probabilistic reverse nearest neighbor query answering
4.5.3 Probabilistic reverse skyline query answering
5. Conclusion
A. Steps to compute the minimum distance
Bibliography
Authors' biographies.
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