{"title":"Dynamic Generalized Closest Pair: Revisiting Eppstein's Technique","authors":"Timothy M. Chan","doi":"10.1137/1.9781611976014.6","DOIUrl":null,"url":null,"abstract":"Eppstein (1995) gave a technique to transform any data structure for dynamic nearest neighbor queries into a data structure for dynamic closest pair, for any distance function; the transformation increases the time bound by two logarithmic factors. We present a similar, simple transformation that is just as good, and can avoid the extra logarithmic factors when the query and update time of the given structure exceed n for some constant ε > 0. Consequently, in the case of an arbitrary distance function, we obtain an optimal O(n)-space data structure to maintain the dynamic closest pair of n points in O(n) amortized time plus O(n) distance evaluations per update.","PeriodicalId":93491,"journal":{"name":"Proceedings of the SIAM Symposium on Simplicity in Algorithms (SOSA)","volume":"16 1","pages":"33-37"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the SIAM Symposium on Simplicity in Algorithms (SOSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1137/1.9781611976014.6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Eppstein (1995) gave a technique to transform any data structure for dynamic nearest neighbor queries into a data structure for dynamic closest pair, for any distance function; the transformation increases the time bound by two logarithmic factors. We present a similar, simple transformation that is just as good, and can avoid the extra logarithmic factors when the query and update time of the given structure exceed n for some constant ε > 0. Consequently, in the case of an arbitrary distance function, we obtain an optimal O(n)-space data structure to maintain the dynamic closest pair of n points in O(n) amortized time plus O(n) distance evaluations per update.