{"title":"基于Vivaldi的结构化点对点网络相似性搜索数据整理与维数压缩","authors":"Yoshihiro Sugaya, K. Motoyama, S. Omachi","doi":"10.1109/ICCE-TW.2015.7216959","DOIUrl":null,"url":null,"abstract":"Peer-to-peer system is a promising solution to manage a large amount of data, but similarity search on peer-to-peer network with a restricted small number of messages is a challenging problem. Existing methods that can perform similarity search work only with low-dimensional data. We propose a method to transform the very high-dimensional data into low-dimensional vectors in order to perform similarity search.","PeriodicalId":340402,"journal":{"name":"2015 IEEE International Conference on Consumer Electronics - Taiwan","volume":"6 35","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data arrangement and dimensional compression using Vivaldi for similarity search on structured peer-to-peer network\",\"authors\":\"Yoshihiro Sugaya, K. Motoyama, S. Omachi\",\"doi\":\"10.1109/ICCE-TW.2015.7216959\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Peer-to-peer system is a promising solution to manage a large amount of data, but similarity search on peer-to-peer network with a restricted small number of messages is a challenging problem. Existing methods that can perform similarity search work only with low-dimensional data. We propose a method to transform the very high-dimensional data into low-dimensional vectors in order to perform similarity search.\",\"PeriodicalId\":340402,\"journal\":{\"name\":\"2015 IEEE International Conference on Consumer Electronics - Taiwan\",\"volume\":\"6 35\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Conference on Consumer Electronics - Taiwan\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCE-TW.2015.7216959\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Consumer Electronics - Taiwan","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCE-TW.2015.7216959","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data arrangement and dimensional compression using Vivaldi for similarity search on structured peer-to-peer network
Peer-to-peer system is a promising solution to manage a large amount of data, but similarity search on peer-to-peer network with a restricted small number of messages is a challenging problem. Existing methods that can perform similarity search work only with low-dimensional data. We propose a method to transform the very high-dimensional data into low-dimensional vectors in order to perform similarity search.