{"title":"在远程空间数据库上近似处理聚合范围查询","authors":"H. Sato, Ryoichi Narita","doi":"10.1504/IJKWI.2013.060275","DOIUrl":null,"url":null,"abstract":"Processing aggregate range queries on remote spatial databases suffers from accessing huge and/or large number of databases that operate autonomously and simple and/or restrictive web API interfaces. To overcome these difficulties, this paper applies a revised version of regular polygon-based search algorithm RPSA to approximately search aggregate range query results over remote spatial databases. The algorithm requests a series of k-NN queries to obtain aggregate range query results. The query point of a subsequent k-NN query is chosen from among the vertices of a regular polygon inscribed in a previously searched circle. Experimental results show that precision is over 0.97 with regard to sum range query results and NOR is at most 4.3. On the other hand, precision is over 0.87 with regard to maximum range query results and NOR is at most 4.9.","PeriodicalId":113936,"journal":{"name":"Int. J. Knowl. Web Intell.","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Approximately processing aggregate range queries on remote spatial databases\",\"authors\":\"H. Sato, Ryoichi Narita\",\"doi\":\"10.1504/IJKWI.2013.060275\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Processing aggregate range queries on remote spatial databases suffers from accessing huge and/or large number of databases that operate autonomously and simple and/or restrictive web API interfaces. To overcome these difficulties, this paper applies a revised version of regular polygon-based search algorithm RPSA to approximately search aggregate range query results over remote spatial databases. The algorithm requests a series of k-NN queries to obtain aggregate range query results. The query point of a subsequent k-NN query is chosen from among the vertices of a regular polygon inscribed in a previously searched circle. Experimental results show that precision is over 0.97 with regard to sum range query results and NOR is at most 4.3. On the other hand, precision is over 0.87 with regard to maximum range query results and NOR is at most 4.9.\",\"PeriodicalId\":113936,\"journal\":{\"name\":\"Int. J. Knowl. Web Intell.\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Knowl. Web Intell.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJKWI.2013.060275\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Knowl. Web Intell.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJKWI.2013.060275","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Approximately processing aggregate range queries on remote spatial databases
Processing aggregate range queries on remote spatial databases suffers from accessing huge and/or large number of databases that operate autonomously and simple and/or restrictive web API interfaces. To overcome these difficulties, this paper applies a revised version of regular polygon-based search algorithm RPSA to approximately search aggregate range query results over remote spatial databases. The algorithm requests a series of k-NN queries to obtain aggregate range query results. The query point of a subsequent k-NN query is chosen from among the vertices of a regular polygon inscribed in a previously searched circle. Experimental results show that precision is over 0.97 with regard to sum range query results and NOR is at most 4.3. On the other hand, precision is over 0.87 with regard to maximum range query results and NOR is at most 4.9.