Tuning the top-k view update process
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Summary
A principled method is presented that complements the inefficiency of the state of the art independently of the statistical propert ies of the data and the characteristics of the update streams.
- Type
- article
- Published
- 2007-01-01
- Cited by
- 2
- References
- 18
- OpenAlex
- https://openalex.org/W14261641
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:7919501
Keywords
Computer science, Inefficiency, Process (computing), State (computer science), Data mining
References
- Student's solutions manual to accompany probability and statistics
- Probability and Statistics with Reliability, Queuing, and Computer Science Applications
- Combining Fuzzy Information from Multiple Systems
- Fuzzy queries in multimedia database systems
- Algorithms and applications for answering ranked queries using ranked views
- Efficient maintenance of materialized top-k views
- Optimal aggregation algorithms for middleware
- Answering top-k queries using views
- Optimizing Multi-Feature Queries for Image Databases
- PREFER: a system for the efficient execution of multi-parametric ranked queries
- Probability and Statistics
- Optimal aggregation algorithms for middleware
- Combining Fuzzy Information from Multiple Systems.
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