{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T10:28:26Z","timestamp":1762165706517,"version":"build-2065373602"},"reference-count":11,"publisher":"Elsevier BV","issue":"5","license":[{"start":{"date-parts":[[2002,3,1]],"date-time":"2002-03-01T00:00:00Z","timestamp":1014940800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2002,3,1]],"date-time":"2002-03-01T00:00:00Z","timestamp":1014940800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Processing Letters"],"published-print":{"date-parts":[[2002,3]]},"DOI":"10.1016\/s0020-0190(01)00236-8","type":"journal-article","created":{"date-parts":[[2002,10,14]],"date-time":"2002-10-14T13:55:05Z","timestamp":1034603705000},"page":"239-246","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["An efficient nearest neighbor search in high-dimensional data spaces"],"prefix":"10.1016","volume":"81","author":[{"given":"Dong-Ho","family":"Lee","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hyoung-Joo","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/S0020-0190(01)00236-8_BIB001","series-title":"Proc. ACM SIGMOD Internat. Conf. on Management of Data","first-page":"47","article-title":"R-trees: A dynamic index structure for spatial searching","author":"Guttman","year":"1984"},{"issue":"1","key":"10.1016\/S0020-0190(01)00236-8_BIB002","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/S0169-023X(00)00009-4","article-title":"SPY-TEC: An efficient indexing method for similarity search in high-dimensional data spaces","volume":"34","author":"Lee","year":"2000","journal-title":"Data Knowledge Engrg."},{"issue":"4","key":"10.1016\/S0020-0190(01)00236-8_BIB003","article-title":"Fast searching by content in multimedia databases","volume":"18","author":"Faloutsos","year":"1995","journal-title":"Data Engrg. Bull."},{"issue":"2","key":"10.1016\/S0020-0190(01)00236-8_BIB004","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1145\/320248.320255","article-title":"Distance browsing in spatial databases","volume":"24","author":"Hjaltason","year":"1999","journal-title":"ACM Trans. Database Systems"},{"issue":"9","key":"10.1016\/S0020-0190(01)00236-8_BIB005","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1145\/361002.361007","article-title":"Multidimensional binary search trees used for associative searching","volume":"18","author":"Bentley","year":"1975","journal-title":"Comm. ACM"},{"key":"10.1016\/S0020-0190(01)00236-8_BIB006","unstructured":"D.H. Lee, H.J. Kim, An efficient nearest neighbor search in high-dimensional data spaces, Seoul National University, CE Technical Report OOPSLA-TR1028, 2000, http:\/\/oopsla.snu.ac.kr\/~dhlee\/OOPSLA-TR1028.ps"},{"key":"10.1016\/S0020-0190(01)00236-8_BIB007","series-title":"Proc. ACM SIGMOD Internat. Conf. on Management of Data","first-page":"71","article-title":"Nearest neighbor queries","author":"Roussopoulos","year":"1995"},{"key":"10.1016\/S0020-0190(01)00236-8_BIB008","series-title":"Proc. 7th Internat. Conf. on Database Theory","first-page":"217","article-title":"When is \u201cNearest Neighbor\u201d meaningful?","author":"Beyer","year":"1999"},{"key":"10.1016\/S0020-0190(01)00236-8_BIB009","series-title":"Proc. ACM SIGMOD Internat. Conf. on Management of Data","article-title":"The pyramid-technique: Towards breaking the curse of dimensionality","author":"Berchtold","year":"1998"},{"key":"10.1016\/S0020-0190(01)00236-8_BIB010","series-title":"ACM PODS Symposium on Principles of Database Systems, Tucson, AZ","article-title":"A cost model for nearest neighbor search in high-dimensional data space","author":"Berchtold","year":"1997"},{"key":"10.1016\/S0020-0190(01)00236-8_BIB011","series-title":"Proc. 22nd Internat. Conf. on Very Large Databases","first-page":"28","article-title":"The X-tree: An indexing structure for high-dimensional data","author":"Berchtold","year":"1996"}],"container-title":["Information Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0020019001002368?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0020019001002368?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T10:20:51Z","timestamp":1762165251000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0020019001002368"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2002,3]]},"references-count":11,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2002,3]]}},"alternative-id":["S0020019001002368"],"URL":"https:\/\/doi.org\/10.1016\/s0020-0190(01)00236-8","relation":{},"ISSN":["0020-0190"],"issn-type":[{"type":"print","value":"0020-0190"}],"subject":[],"published":{"date-parts":[[2002,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"An efficient nearest neighbor search in high-dimensional data spaces","name":"articletitle","label":"Article Title"},{"value":"Information Processing Letters","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/S0020-0190(01)00236-8","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"converted-article","name":"content_type","label":"Content Type"},{"value":"Copyright \u00a9 2002 Elsevier Science B.V. All rights reserved.","name":"copyright","label":"Copyright"}]}}