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Abstract: This paper outlines a general learning approach to the knowledge acquisition problem of semantic query optimization. The results shows that the learned rules outperformed hand-coded rules and provided significant savings. For more detailed description of the approaches discussed in this paper, please refer to the author's doctoral dissertation [2]. Other references are available upon request. (Update)
Context of citations to this paper: More
...to maximize the net utility of learning. Using Robustness Values for Resource Control I have developed a general solution (Hsu 1996) to deal with the tradeoff in the rule induction for SQO. The solution is to develop an approach to estimating the degree of...
...the optimizer can still be used with minimal modification. Many algorithms are available for learning useful semantic knowledge [16, 22, 19, 23, 24, 25]. 1.1 Query Plans A query plan is a directed acyclic graph with its nodes as plan steps and its edges as the ordering...
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BibTeX entry: (Update)
Hsu, C.-N. 1996. Learning Effective and Robust Knowledge for Semantic Query Optimization. Ph.D. Dissertation, Department of Computer Science, University of Southern California. http://citeseer.ist.psu.edu/article/hsu96learning.html More
@misc{ hsu96learning,
author = "C. Hsu",
title = "Learning Effective and Robust Knowledge for Semantic Query Optimization",
text = "Hsu, C.-N. 1996. Learning Effective and Robust Knowledge for Semantic Query
Optimization. Ph.D. Dissertation, Department of Computer Science, University
of Southern California.",
year = "1996",
url = "citeseer.ist.psu.edu/article/hsu96learning.html" }
Citations (may not include all citations):5 AAAI Press (context) - the, Conference et al. - 1996
3 Retrieving and integrating data from multiple information so.. (context) - Knoblock - 1993
1 University of Southern California (context) - Computer - 1996
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