Categorical data skyline using classification tree

Wookey Lee, Justin Jongsu Song, Carson K.S. Leung

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

Skyline query is an effective method to process large-sized multi-dimensional 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.

Original languageEnglish
Title of host publicationWeb Technologies and Applications - 13th Asia-Pacific Web Conference, APWeb 2011, Proceedings
Pages181-187
Number of pages7
DOIs
StatePublished - 2011
Event13th Asia-Pacific Conference on Web Technology, APWeb 2011 - Beijing, China
Duration: 18 Apr 201120 Apr 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6612 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th Asia-Pacific Conference on Web Technology, APWeb 2011
Country/TerritoryChina
CityBeijing
Period18/04/1120/04/11

Keywords

  • Skyline
  • categorical data
  • classification tree
  • domination

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