Efficient Processing of Top-k Queries in Uncertain Databases with x-Relations

This work introduces novel polynomial algorithms for processing top-k queries in uncertain databases under the generally adopted model of x-relations. An x-relation consists of a number of x-tuples, and each x-tuple randomly instantiates into one tuple from one or more alternatives. Our results sign...

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Vydáno v:IEEE transactions on knowledge and data engineering Ročník 20; číslo 12; s. 1669 - 1682
Hlavní autoři: Ke Yi, Feifei Li, Kollios, G., Srivastava, D.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York, NY IEEE 01.12.2008
IEEE Computer Society
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithmics. Computability. Computer arithmetics
Algorithms
Analysis of Algorithms and Problem Complexity
Applied sciences
Cleaning
Complexity
Computer science; control theory; systems
Data models
Data processing. List processing. Character string processing
Database design
Database Management
Exact sciences and technology
Information systems. Data bases
Information Technology and Systems
Mathematical models
Memory organisation. Data processing
modeling and management
Polynomials
Power system modeling
Probability distribution
Queries
Query design and implementation languages
Query processing
Runtime
Software
Theoretical computing
Theory of Computation
Top-k Query
Uncertain Database
Uncertainty
Web server
x-Relation Model
Top-k Query
Analysis of Algorithms and Problem Complexity
Uncertain Database
Database design
Query design and implementation languages
x-Relation Model
Database Management
Theory of Computation
Information Technology and Systems
modeling and management
Probabilistic approach
Database query
Hierarchical classification
top-k
Relational database
Linear time
probabilistic data
Polynomial method
Modeling
Algorithm
Polynomial time
Uncertain system
Query processing
Algorithm complexity
Database
x-relation
uncertain database
Time complexity
ISSN:1041-4347, 1558-2191
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Shrnutí:This work introduces novel polynomial algorithms for processing top-k queries in uncertain databases under the generally adopted model of x-relations. An x-relation consists of a number of x-tuples, and each x-tuple randomly instantiates into one tuple from one or more alternatives. Our results significantly improve the best known algorithms for top-k query processing in uncertain databases, in terms of both runtime and memory usage. In the single-alternative case, the new algorithms are 2 to 3 orders of magnitude faster than the previous algorithms. In the multialternative case, we introduce the first-known polynomial algorithms, while the current best algorithms have exponential complexity in both time and space. Our algorithms run in near linear or low polynomial time and cover both types of top-k queries in uncertain databases. We provide both the theoretical analysis and an extensive experimental evaluation to demonstrate the superiority of the new approaches over existing solutions.
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ISSN:1041-4347
1558-2191
DOI:10.1109/TKDE.2008.90