Jun Feng, Chunyan Lu, Shimin Xu, Toyohide Watanabe
{"title":"DynSketch:一个用于道路网络中移动物体的时空聚合索引","authors":"Jun Feng, Chunyan Lu, Shimin Xu, Toyohide Watanabe","doi":"10.1504/IJIDSS.2009.028646","DOIUrl":null,"url":null,"abstract":"Recently, many spatio-temporal applications pay attention to the summarised information of moving objects in road networks (e.g., the number of vehicles, the average speed). Existing sketch method can solve the distinct counting problem, but without provable guarantees on the approximate quality of aggregate queries over moving objects in road networks in all situations. This paper proposes a dynamic sketch method (DynSketch index) by using existing histogram technique to intelligently partition the sketch method, and to improve the quality of the approximation. Evaluation shows this new method outperforms the sketch method in space consumption, queries efficiency, approximate errors control, and does well in small region queries especially.","PeriodicalId":311979,"journal":{"name":"Int. J. Intell. Def. Support Syst.","volume":"96 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"DynSketch: a spatio-temporal aggregate index for moving objects in road networks\",\"authors\":\"Jun Feng, Chunyan Lu, Shimin Xu, Toyohide Watanabe\",\"doi\":\"10.1504/IJIDSS.2009.028646\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, many spatio-temporal applications pay attention to the summarised information of moving objects in road networks (e.g., the number of vehicles, the average speed). Existing sketch method can solve the distinct counting problem, but without provable guarantees on the approximate quality of aggregate queries over moving objects in road networks in all situations. This paper proposes a dynamic sketch method (DynSketch index) by using existing histogram technique to intelligently partition the sketch method, and to improve the quality of the approximation. Evaluation shows this new method outperforms the sketch method in space consumption, queries efficiency, approximate errors control, and does well in small region queries especially.\",\"PeriodicalId\":311979,\"journal\":{\"name\":\"Int. J. Intell. Def. Support Syst.\",\"volume\":\"96 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Intell. Def. Support Syst.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJIDSS.2009.028646\",\"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. Intell. Def. Support Syst.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJIDSS.2009.028646","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
DynSketch: a spatio-temporal aggregate index for moving objects in road networks
Recently, many spatio-temporal applications pay attention to the summarised information of moving objects in road networks (e.g., the number of vehicles, the average speed). Existing sketch method can solve the distinct counting problem, but without provable guarantees on the approximate quality of aggregate queries over moving objects in road networks in all situations. This paper proposes a dynamic sketch method (DynSketch index) by using existing histogram technique to intelligently partition the sketch method, and to improve the quality of the approximation. Evaluation shows this new method outperforms the sketch method in space consumption, queries efficiency, approximate errors control, and does well in small region queries especially.