{"title":"辅助存储器的全动态度量访问方法","authors":"Roberto Uribe, G. Navarro","doi":"10.1109/SISAP.2009.20","DOIUrl":null,"url":null,"abstract":"We introduce a novel metric space search data structure called EGNAT, which is fully dynamic and designed for secondary memory. The EGNAT is based on Brin's GNAT static index, and partitions the space according to hyperplanes. The EGNAT implements deletions using a novel technique dubbed Ghost Hyperplanes, which is of independent interest for other metric space indexes. We show experimentally that the EGNAT is competitive with the M-tree, the baseline for this scenario.","PeriodicalId":130242,"journal":{"name":"2009 Second International Workshop on Similarity Search and Applications","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"EGNAT: A Fully Dynamic Metric Access Method for Secondary Memory\",\"authors\":\"Roberto Uribe, G. Navarro\",\"doi\":\"10.1109/SISAP.2009.20\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce a novel metric space search data structure called EGNAT, which is fully dynamic and designed for secondary memory. The EGNAT is based on Brin's GNAT static index, and partitions the space according to hyperplanes. The EGNAT implements deletions using a novel technique dubbed Ghost Hyperplanes, which is of independent interest for other metric space indexes. We show experimentally that the EGNAT is competitive with the M-tree, the baseline for this scenario.\",\"PeriodicalId\":130242,\"journal\":{\"name\":\"2009 Second International Workshop on Similarity Search and Applications\",\"volume\":\"73 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Second International Workshop on Similarity Search and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SISAP.2009.20\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Second International Workshop on Similarity Search and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SISAP.2009.20","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
EGNAT: A Fully Dynamic Metric Access Method for Secondary Memory
We introduce a novel metric space search data structure called EGNAT, which is fully dynamic and designed for secondary memory. The EGNAT is based on Brin's GNAT static index, and partitions the space according to hyperplanes. The EGNAT implements deletions using a novel technique dubbed Ghost Hyperplanes, which is of independent interest for other metric space indexes. We show experimentally that the EGNAT is competitive with the M-tree, the baseline for this scenario.
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