Tertiary hash tree-based index structure for high dimensional multimedia data
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tak, Yoon-Sik | - |
dc.contributor.author | Rho, Seungmin | - |
dc.contributor.author | Hwang, Eenjun | - |
dc.contributor.author | Lee, Hanku | - |
dc.date.accessioned | 2021-09-06T13:45:58Z | - |
dc.date.available | 2021-09-06T13:45:58Z | - |
dc.date.created | 2021-06-15 | - |
dc.date.issued | 2012-11 | - |
dc.identifier.issn | 1380-7501 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/107047 | - |
dc.description.abstract | Dominant features for the content-based image retrieval usually have high-dimensionality. So far, many researches have been done to index such values to support fast retrieval. Still, many existing indexing schemes are suffering from performance degradation due to the curse of dimensionality problem. As an alternative, heuristic algorithms have been proposed to calculate the answer with 'high probability' at the cost of accuracy. In this paper, we propose a new hash tree-based indexing structure called tertiary hash tree for indexing high-dimensional feature data. Tertiary hash tree provides several advantages compared to the traditional extendible hash structure in terms of resource usage and search performance. Through extensive experiments, we show that our proposed index structure achieves outstanding performance. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER | - |
dc.title | Tertiary hash tree-based index structure for high dimensional multimedia data | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Hwang, Eenjun | - |
dc.identifier.doi | 10.1007/s11042-010-0687-8 | - |
dc.identifier.scopusid | 2-s2.0-84864042956 | - |
dc.identifier.wosid | 000306345000004 | - |
dc.identifier.bibliographicCitation | MULTIMEDIA TOOLS AND APPLICATIONS, v.61, no.1, pp.51 - 68 | - |
dc.relation.isPartOf | MULTIMEDIA TOOLS AND APPLICATIONS | - |
dc.citation.title | MULTIMEDIA TOOLS AND APPLICATIONS | - |
dc.citation.volume | 61 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 51 | - |
dc.citation.endPage | 68 | - |
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.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Software Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordAuthor | Tertiary hash tree | - |
dc.subject.keywordAuthor | Extendible hash | - |
dc.subject.keywordAuthor | Content-based | - |
dc.subject.keywordAuthor | Image retrieval | - |
dc.subject.keywordAuthor | Multidimensional data | - |
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.