DC Field | Value | Language |
---|---|---|
dc.contributor.author | Roh, Yohan J. | ko |
dc.contributor.author | Kim, Jae Ho | ko |
dc.contributor.author | Son, Jin Hyun | ko |
dc.contributor.author | Kim, Myoung Ho | ko |
dc.date.accessioned | 2013-03-09T21:46:35Z | - |
dc.date.available | 2013-03-09T21:46:35Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2011-12 | - |
dc.identifier.citation | DECISION SUPPORT SYSTEMS, v.52, no.1, pp.82 - 94 | - |
dc.identifier.issn | 0167-9236 | - |
dc.identifier.uri | http://hdl.handle.net/10203/97556 | - |
dc.description.abstract | Histograms can be useful in estimating the selectivity of queries in areas such as database query optimization and data exploration. In this paper, we propose a new histogram method for multidimensional data, called the Q-Histogram, based on the use of the quad-tree, which is a popular index structure for multidimensional data sets. The use of the compact representation of the target data obtainable from the quad-tree allows a fast construction of a histogram with the minimum number of scanning, i.e., only one scanning, of the underlying data. In addition to the advantage of computation time, the proposed method also provides a better performance than other existing methods with respect to the quality of selectivity estimation. We present a new measure of data skew for a histogram bucket, called the weighted bucket skew. Then, we provide an effective technique for skew-tolerant organization of histograms. Finally, we compare the accuracy and efficiency of the proposed method with other existing methods using both real-life data sets and synthetic data sets. The results of experiments show that the proposed method generally provides a better performance than other existing methods in terms of accuracy as well as computational efficiency. Crown Copyright (C) 2011 Published by Elsevier B.V. All rights reserved. | - |
dc.language | English | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.subject | QUERIES | - |
dc.subject | OPTIMIZATION | - |
dc.subject | SELECTIVITY | - |
dc.subject | ALGORITHMS | - |
dc.title | Efficient construction of histograms for multidimensional data using quad-trees | - |
dc.type | Article | - |
dc.identifier.wosid | 000297889400009 | - |
dc.identifier.scopusid | 2-s2.0-80455174038 | - |
dc.type.rims | ART | - |
dc.citation.volume | 52 | - |
dc.citation.issue | 1 | - |
dc.citation.beginningpage | 82 | - |
dc.citation.endingpage | 94 | - |
dc.citation.publicationname | DECISION SUPPORT SYSTEMS | - |
dc.contributor.localauthor | Kim, Myoung Ho | - |
dc.contributor.nonIdAuthor | Roh, Yohan J. | - |
dc.contributor.nonIdAuthor | Kim, Jae Ho | - |
dc.contributor.nonIdAuthor | Son, Jin Hyun | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Data management | - |
dc.subject.keywordAuthor | Query optimization | - |
dc.subject.keywordAuthor | Selectivity estimation | - |
dc.subject.keywordAuthor | Multidimensional histograms | - |
dc.subject.keywordPlus | QUERIES | - |
dc.subject.keywordPlus | OPTIMIZATION | - |
dc.subject.keywordPlus | SELECTIVITY | - |
dc.subject.keywordPlus | ALGORITHMS | - |
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