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All Nearest Neighbors Query including Scores Road Network
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dc.contributor.authorKim, Hyo Kyun-
dc.contributor.authorChung, Tae Sun-
dc.date.issued2020-12-01-
dc.identifier.urihttps://aurora.ajou.ac.kr/handle/2018.oak/36562-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85113362657&origin=inward-
dc.description.abstractThis paper introduces an improved ANN (All Nearest Neighbor) algorithm using the SCL (Standard Clustered Loop) algorithm to reduce the consumption of computing resources that can occur when searching for the data object nearest to the query object in the process of executing the algorithm. Additionally, a method to improve ANN algorithm is proposed. When the algorithm is executed, it is a situation in which the user finds a data object adjacent to the user. In this case, our technique applies the criteria set provided by users.-
dc.description.sponsorshipACKNOWLEDGMENT This research was supported by the MIST(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW supervised by the IITP (Institute for Information & communications Technology Promotion) (20150009080031001).-
dc.language.isoeng-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.subject.meshAll nearest neighbors-
dc.subject.meshANN algorithm-
dc.subject.meshComputing resource-
dc.subject.meshData objects-
dc.subject.meshQuery object-
dc.subject.meshRoad network-
dc.titleAll Nearest Neighbors Query including Scores Road Network-
dc.typeConference-
dc.citation.conferenceDate2020.12.16. ~ 2020.12.18.-
dc.citation.conferenceName2020 International Conference on Computational Science and Computational Intelligence, CSCI 2020-
dc.citation.editionProceedings - 2020 International Conference on Computational Science and Computational Intelligence, CSCI 2020-
dc.citation.endPage1424-
dc.citation.startPage1423-
dc.citation.titleProceedings - 2020 International Conference on Computational Science and Computational Intelligence, CSCI 2020-
dc.identifier.bibliographicCitationProceedings - 2020 International Conference on Computational Science and Computational Intelligence, CSCI 2020, pp.1423-1424-
dc.identifier.doi10.1109/csci51800.2020.00265-
dc.identifier.scopusid2-s2.0-85113362657-
dc.identifier.urlhttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9457837-
dc.subject.keywordANN-
dc.subject.keywordnearest neighbor-
dc.subject.keywordroad network-
dc.type.otherConference Paper-
dc.description.isoafalse-
dc.subject.subareaArtificial Intelligence-
dc.subject.subareaComputer Networks and Communications-
dc.subject.subareaSafety, Risk, Reliability and Quality-
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