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Skyline Query Algorithm in the Categoric Data  

Lee, Woo-Key (인하대학교 산업공학과)
Choi, Jung-Ho (인하대학교 산업공학과)
Song, Jong-Su (인하대학교 산업공학과)
Publication Information
Journal of KIISE:Computing Practices and Letters / v.16, no.7, 2010 , pp. 819-823 More about this Journal
Abstract
The skyline query is one of the effective methods to deal with the large amounts and multi-dimensional data set. By utilizing the concept of 'dominate' the skyline query can pinpoint the target data so that the dominated ones, about 95% of them, can efficiently be excluded as an unnecessary data. Most of the skyline query algorithms, however, have been developed in terms of the numerical data set. This paper pioneers an entirely new domain, the categorical data, on which the corresponding ranking measures for the skyline queries are suggested. In the experiment, the ACM Computing Classification System has been exploited to which our methods are significantly represented with respect to performance thresholds such as the processing time and precision ratio, etc.
Keywords
skyline; categorical data; domination;
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