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Generating high dimensional data and query sets
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kim, Sang-Wook | - |
| dc.contributor.author | Yoon, Seok-Ho | - |
| dc.contributor.author | Lee, Sang-Cheo | - |
| dc.contributor.author | Lee, Junghoon | - |
| dc.contributor.author | Shin, Miyoung | - |
| dc.date.accessioned | 2022-12-21T09:28:57Z | - |
| dc.date.available | 2022-12-21T09:28:57Z | - |
| dc.date.created | 2022-09-16 | - |
| dc.date.issued | 2007-01 | - |
| dc.identifier.issn | 0302-9743 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/180538 | - |
| dc.description.abstract | Previous researches on multidimensional indexes typically have used synthetic data sets distributed uniformly or normally over multidimensional space for performance evaluation. These kinds of data sets hardly reflect the characteristics of multimedia database applications. In this paper, we discuss issues on generating high dimensional data and query sets for resolving the problem. We first identify the requirements of the data and query sets for fair performance evaluation of multidimensional indexes, and then propose HDDQ.Gen (High-Dimensional Data and Query Generator) that satisfies such requirements. HDDQ-Gen has the following features: (1) clustered distribution, (2) various object distribution in each cluster, (3) various cluster distribution, (4) various correlations among different dimensions, and (5) query distribution depending on data distribution. Using these features, users are able to control the distribution characteristics of data and query sets appropriate for their target applications. | - |
| dc.language | 영어 | - |
| dc.language.iso | en | - |
| dc.publisher | Springer Verlag | - |
| dc.title | Generating high dimensional data and query sets | - |
| dc.type | Article | - |
| dc.contributor.affiliatedAuthor | Kim, Sang-Wook | - |
| dc.identifier.doi | 10.1007/978-3-540-69507-3_30 | - |
| dc.identifier.scopusid | 2-s2.0-38149093163 | - |
| dc.identifier.bibliographicCitation | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.4362 LNCS, pp.357 - 366 | - |
| dc.relation.isPartOf | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
| dc.citation.title | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
| dc.citation.volume | 4362 LNCS | - |
| dc.citation.startPage | 357 | - |
| dc.citation.endPage | 366 | - |
| dc.type.rims | ART | - |
| dc.type.docType | Conference Paper | - |
| dc.description.journalClass | 1 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.subject.keywordPlus | Cluster analysis | - |
| dc.subject.keywordPlus | Distributed computer systems | - |
| dc.subject.keywordPlus | Multimedia systems | - |
| dc.subject.keywordPlus | Query languages | - |
| dc.subject.keywordPlus | High dimensional data | - |
| dc.subject.keywordPlus | Query distribution | - |
| dc.subject.keywordPlus | Query sets | - |
| dc.subject.keywordPlus | Data structures | - |
| dc.identifier.url | https://link.springer.com/chapter/10.1007/978-3-540-69507-3_30 | - |
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Related Researcher
- Kim, Sang-Wook
- COLLEGE OF ENGINEERING (SCHOOL OF COMPUTER SCIENCE)