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ANSWERING WHY-NOT QUESTIONS ON REVERSE SKYLINE QUERIES OVER INCOMPLETE DATA

JUTI: Jurnal Ilmiah Teknologi Informasi · Vol. 17 No. 1 (2019) · pp. 84–93

DOI
10.12962/j24068535.v17i1.a824
ISSN
2406-8535, 1412-6389
Published
2019-03-12
Publisher
Institut Teknologi Sepuluh Nopember
Language
eng

Abstract

Recently, the development of the query-based preferences has received considerable attention from researchers and data users. One of the most popular preference-based queries is the skyline query, which will give a subset of superior records that are not dominated by any other records. As the developed version of skyline queries, a reverse skyline query rise. This query aims to get information about the query points that make a data or record as the part of result of their skyline query. Furthermore, data-oriented IT development requires scientists to be able to process data in all conditions. In the real world, there exist incomplete multidimensional data, both because of damage, loss, and privacy. In order to increase the usability over a data set, this study will discuss one of the problems in processing reverse skyline queries over incomplete data, namely the "why-not" problem. The considered solution to this "why-not" problem is advice and steps so that a query point that does not initially consider an incomplete data, as a result, can later make the record or incomplete data as part of the results. In this study, there will be further discussion about the dominance relationship between incomplete data along with the solution of the problem. Moreover, some performance evaluations are conducted to measure the level of efficiency and effectiveness.

Collaboration network of the authors

8 authors · 11 co-authorship links

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  • Institut Teknologi Sepuluh Nopember
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Tohari AhmadInstitut Teknologi Sepuluh Nopember1
Vynska Amalia PermadiAffiliation unknown1
Syukron Rifail MuttaqiAffiliation unknown1
Henning Titi CiptaningtyasInstitut Teknologi Sepuluh Nopember1
Hafara FirdausiInstitut Teknologi Sepuluh Nopember1
Rohana QudusInstitut Teknologi Sepuluh Nopember1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://juti.if.its.ac.id/index.php/juti/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">ANSWERING WHY-NOT QUESTIONS ON REVERSE SKYLINE QUERIES OVER INCOMPLETE DATA</dc:title>
	<dc:creator xml:lang="en">Santoso, Bagus Jati</dc:creator>
	<dc:creator xml:lang="en">Connery, Tosca Yoel</dc:creator>
	<dc:description xml:lang="en">        Recently, the development of the query-based preferences has received considerable attention from researchers and data users. One of the most popular preference-based queries is the skyline query, which will give a subset of superior records that are not dominated by any other records. As the developed version of skyline queries, a reverse skyline query rise. This query aims to get information about the query points that make a data or record as the part of result of their skyline query.     Furthermore, data-oriented IT development requires scientists to be able to process data in all conditions. In the real world, there exist incomplete multidimensional data, both because of damage, loss, and privacy. In order to increase the usability over a data set, this study will discuss one of the problems in processing reverse skyline queries over incomplete data, namely the "why-not" problem. The considered solution to this "why-not" problem is advice and steps so that a query point that does not initially consider an incomplete data, as a result, can later make the record or incomplete data as part of the results. In this study, there will be further discussion about the dominance relationship between incomplete data along with the solution of the problem. Moreover, some performance evaluations are conducted to measure the level of efficiency and effectiveness.</dc:description>
	<dc:publisher xml:lang="en">Institut Teknologi Sepuluh Nopember</dc:publisher>
	<dc:date>2019-03-12</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://juti.if.its.ac.id/index.php/juti/article/view/824</dc:identifier>
	<dc:identifier>10.12962/j24068535.v17i1.a824</dc:identifier>
	<dc:source xml:lang="en">JUTI: Jurnal Ilmiah Teknologi Informasi; Vol 17, No. 1, Januari 2019; 84-93</dc:source>
	<dc:source>2406-8535</dc:source>
	<dc:source>1412-6389</dc:source>
	<dc:source>10.12962/j24068535.v17i1</dc:source>
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	<dc:relation>https://juti.if.its.ac.id/index.php/juti/article/view/824/387</dc:relation>
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