{"title":"一种用于Hamming空间快速范围搜索的索引结构","authors":"E. M. Reina, K. Pu, F. Qureshi","doi":"10.1109/CRV.2017.37","DOIUrl":null,"url":null,"abstract":"This paper addresses the problem of indexing and querying very large databases of binary vectors. Such databases of binary vectors are a common occurrence in domains such as information retrieval and computer vision. We propose an indexing structure consisting of a compressed bitwise trie and a hash table for supporting range queries in Hamming space. The index structure, which can be updated incrementally, is able to solve the range queries for any radius. Our approach significantly outperforms state-of-the-art approaches.","PeriodicalId":308760,"journal":{"name":"2017 14th Conference on Computer and Robot Vision (CRV)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An Index Structure for Fast Range Search in Hamming Space\",\"authors\":\"E. M. Reina, K. Pu, F. Qureshi\",\"doi\":\"10.1109/CRV.2017.37\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper addresses the problem of indexing and querying very large databases of binary vectors. Such databases of binary vectors are a common occurrence in domains such as information retrieval and computer vision. We propose an indexing structure consisting of a compressed bitwise trie and a hash table for supporting range queries in Hamming space. The index structure, which can be updated incrementally, is able to solve the range queries for any radius. Our approach significantly outperforms state-of-the-art approaches.\",\"PeriodicalId\":308760,\"journal\":{\"name\":\"2017 14th Conference on Computer and Robot Vision (CRV)\",\"volume\":\"54 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 14th Conference on Computer and Robot Vision (CRV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CRV.2017.37\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 14th Conference on Computer and Robot Vision (CRV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRV.2017.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Index Structure for Fast Range Search in Hamming Space
This paper addresses the problem of indexing and querying very large databases of binary vectors. Such databases of binary vectors are a common occurrence in domains such as information retrieval and computer vision. We propose an indexing structure consisting of a compressed bitwise trie and a hash table for supporting range queries in Hamming space. The index structure, which can be updated incrementally, is able to solve the range queries for any radius. Our approach significantly outperforms state-of-the-art approaches.