Categorical data skyline using classification tree

Authors:
Wookey Lee;Justin JongSu Song;Carson K.-S. Leung
Affiliations:
Department of Industrial Engineering, Inha University, South Korea;Department of Industrial Engineering, Inha University, South Korea;Department of Computer Science, The University of Manitoba, Canada
Venue:
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Year:
2011

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Abstract

Skyline query is an effective method to process large-sized multidimensional data sets as it can pinpoint the target data so that dominated data (say, 95% of data) can be efficiently excluded as unnecessary data objects. However, most of the conventional skyline algorithms were developed to handle numerical data. Thus, most of the text data were excluded from being processed by the algorithms. In this paper, we pioneer an entirely new domain for skyline query--namely, the categorical data--with which the corresponding ranking measures for the skyline queries are developed. We tested our proposed algorithm using the ACM Computing Classification System.