Banchong Harangsri, John Shepherd, and Anne H. H. Ngu. Query size estimation using machine learning. In Database Systems for Advanced Applications, pages 97{ 106, 1997. Home/Search Document Details and Download
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Query Size Estimation using Systematic Sampling - Banchong Harangsri (1996) Self-citation (Harangsri Shepherd Ngu) (Correct)
....of the summary relation follows much closer to the actual frequency distributions in the source relation. Curve Fitting The methods [23, 5] in this class are based on using polynomial regression to find the best fit set of coefficients to minimise the criterion of least squared error. Recently [9], we have proposed the use of a learning machine called M5 [20] which combines model based learning and instance based learning [14, 1, 2] Using feedback from user queries (instances) a regression tree [4] is created whose leaf nodes consist of linear regression functions. When a new query is ....
....to estimate its size, the most similar queries to the new query are picked up from the stored user queries and the result size of the new query is calculated based on (1) some linear regression functions of the regression tree and (2) the actual result sizes of the most similar queries. In [9], we compared the performance of M5 and a curvefitting method called ASE (Adaptive Selectivity Estimation) 5] It appeared that M5 significantly outperformed ASE. These curve fitting methods can deal very well with queries with simple selections (i.e. whose selection predicates specify on a ....
B. Harangsri, J. Shepherd, and A. Ngu. Query Size Estimation using Machine Learning. In 1996 International Computer Symposium (ICS '96), December 19--21, 1996 National Sun Yat-Sen University Kaohsiung, Taiwan, R.O.C. 1996. To be published.
Query Size Estimation using Machine Learning - Banchong Harangsri (1996) (1 citation) Self-citation (Harangsri Shepherd Ngu) (Correct)
....Estimation using Machine Learning Banchong Harangsri John Shepherd Anne Ngu School of Computer Science and Engineering, The University of New South Wales, Sydney 2052, AUSTRALIA. Telephone: 61 2 385 3980 Fax: 61 2 385 1813 Email: fbjtong,jas,anneg cse.unsw.edu.au Abstract In a previous paper [6], we introduced the notion of using machine learning techniques to solve the problem of query size estimation in database query optimisation. In this paper, we build on this work by describing a new generic algorithm to correct the training set of queries for our machine learning method in ....
....join, but we assume here that there is some way to extract only the simple operations from these queries. 3 Size Estimation with Retrieval Queries In this section, we summarise our method of using machine learning to solve the query size estimation problem; this method is described in detail in [6]. The machine learning mechanism that we use is a combination of model based learning and instancebased learning originally proposed by Quinlan [15] It involves construction of a model tree, a kind of regression tree originally proposed by Breiman et al. 1] Our implementation of the method ....
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B. Harangsri, J. Shepherd and A. Ngu. Query Size Estimation using Machine Learning. In Proceedings of the 1996 International Conference on Artificial Intelligence (TAAI-96) (joint with 1996 International Computer Symposium (ICS'96)), National Sun Yat-Sen University, Kaohsiung, Taiwan, R.O.C., December 1996.
A Learning-Based Approach to Estimate Statistics of.. - Gao, Wang, Wang.. (2003) (Correct)
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Banchong Harangsri, John Shepherd, and Anne H. H. Ngu. Query size estimation using machine learning. In Database Systems for Advanced Applications, pages 97{ 106, 1997.
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