332 77

Full metadata record

DC FieldValueLanguage
dc.contributor.author원정임-
dc.date.accessioned2021-03-09T01:13:19Z-
dc.date.available2021-03-09T01:13:19Z-
dc.date.issued2019-06-
dc.identifier.citationCOMPUTER SCIENCE AND INFORMATION SYSTEMS, v. 16, no. 2, page. 615-638en_US
dc.identifier.issn1820-0214-
dc.identifier.urihttp://www.doiserbia.nb.rs/Article.aspx?ID=1820-02141900012J#.X8B7UNAzaUk-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/160278-
dc.description.abstractThe Earth Mover's Distance (EMD) is one of the most-widely used distance functions to measure the similarity between two multimedia objects. While providing good search results, the EMD is too much time consuming to be used in large multimedia databases. To solve the problem, we propose an approximate k-nearest neighbor (k-NN) search method based on the EMD. In the proposed method, the overhead for both disk accesses and EMD computations is reduced significantly, thanks to the approximation. First, the proposed method builds an index using the M-tree, a distance-based multi-dimensional index structure, to reduce the disk access overhead. When building the index, we reduce the number of features in the multimedia objects through dimensionality-reduction. When performing the k-NN search on the M-tree, we find a small set of candidates from the disk using the index and then perform the post-processing on them. Second, the proposed method uses the approximate EMD for index retrieval and post-processing to reduce the computational overhead of the EMD. To compensate the errors due to the approximation, the method provides a way of accuracy improvement of the approximate EMD. We performed extensive experiments to show the efficiency of the proposed method. As a result, the method achieves significant improvement in performance with only small errors: the proposed method outperforms the previous method by up to 67.3% with only 3.5% error.en_US
dc.description.sponsorshipThis research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2017R1D1A1B03030969). This research was supported by the MSIT (Ministry of Science, ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-20182013-1-00881) supervised by the IITP (Institute for Information & communication Technology Promotion) and supported by Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (No. NRF-2017M3C4A7083678).en_US
dc.language.isoenen_US
dc.publisherCOMSIS CONSORTIUMen_US
dc.subjectEarth mover's distanceen_US
dc.subjectcontent-based information retrievalen_US
dc.subjectk-nearest neighbor queryen_US
dc.titleOn Approximate k-Nearest Neighbor Searches Based on the Earth Mover’s Distance for Efficient Content-Based Multimedia Information Retrievalen_US
dc.typeArticleen_US
dc.identifier.doi10.2298/CSIS181010012-
dc.relation.journalCOMPUTER SCIENCE AND INFORMATION SYSTEMS-
dc.contributor.googleauthorJang, Min-Hee-
dc.contributor.googleauthorKim, Sang-Wook-
dc.contributor.googleauthorLoh, Woong-Kee-
dc.contributor.googleauthorWon, Jung-Im-
dc.relation.code2019038673-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF ENGINEERING[S]-
dc.sector.departmentCENTER FOR INNOVATION IN ENGINEERING EDUCATION-
dc.identifier.pidjiwon-


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE