Efficient skycube computation using point and domain-based filtering
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kailasam, Gayathri Tambaram | - |
dc.contributor.author | Lee, Jin-Seung | - |
dc.contributor.author | Rhee, Jae-Won | - |
dc.contributor.author | Kang, Jaewoo | - |
dc.date.accessioned | 2021-09-08T03:57:50Z | - |
dc.date.available | 2021-09-08T03:57:50Z | - |
dc.date.created | 2021-06-11 | - |
dc.date.issued | 2010-04-01 | - |
dc.identifier.issn | 0020-0255 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/116651 | - |
dc.description.abstract | Skyline queries have been increasingly used in multi-criteria decision making and data mining applications. They retrieve a set of interesting points from a potentially large set of data points. A point is said to be interesting if it is not dominated by any other point. Skyline cube (skycube) consists of skylines of all possible non-empty subsets of a given set of dimensions. In this paper, we propose two algorithms for computing skycube using bitmaps that are derivable from indexes. The Point-based skycube algorithm is an improvement over the existing Bitmap algorithm, extended to compute skycube. The Point-based algorithm processes one point at a time to check for skylines in all subspaces. The Domain-based skycube algorithm views points as value combinations and probes entire search space for potential skyline points. It significantly reduces bitmap access for low cardinality, dimensions. Our experimental study shows that the two algorithms strictly dominate, or at least comparable to, the current skycube algorithm in most of the cases, suggesting that such an approach could be a useful addition to the set of skyline query processing techniques. (C) 2009 Elsevier Inc. All rights reserved. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCIENCE INC | - |
dc.subject | SKYLINE | - |
dc.title | Efficient skycube computation using point and domain-based filtering | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kang, Jaewoo | - |
dc.identifier.doi | 10.1016/j.ins.2009.11.040 | - |
dc.identifier.scopusid | 2-s2.0-73749085171 | - |
dc.identifier.wosid | 000275073300002 | - |
dc.identifier.bibliographicCitation | INFORMATION SCIENCES, v.180, no.7, pp.1090 - 1103 | - |
dc.relation.isPartOf | INFORMATION SCIENCES | - |
dc.citation.title | INFORMATION SCIENCES | - |
dc.citation.volume | 180 | - |
dc.citation.number | 7 | - |
dc.citation.startPage | 1090 | - |
dc.citation.endPage | 1103 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.subject.keywordPlus | SKYLINE | - |
dc.subject.keywordAuthor | Database | - |
dc.subject.keywordAuthor | Skycube | - |
dc.subject.keywordAuthor | Skyline | - |
dc.subject.keywordAuthor | Algorithm | - |
dc.subject.keywordAuthor | Index | - |
dc.subject.keywordAuthor | Multidimensional data structures | - |
dc.subject.keywordAuthor | Multi-criteria decision making | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.