{"title":"一种基于聚合查询的时空预测方法","authors":"Jun Feng, Zhonghua Zhu, Yaqing Shi, Liming Xu","doi":"10.1504/IJKWI.2013.052723","DOIUrl":null,"url":null,"abstract":"The prediction of spatio-temporal data streams which is based on aggregate queries has been an important research direction in the research field of databases. More and more methods have been proposed to obtain approximate aggregate results. However, they will consume a lot of time and storage space. This paper proposes Dynamic Sketch DS index by using modified method of Adaptive Multi-dimensional Histogram AMH* to intelligently partition static sketch which can improve the approximate quality of aggregate queries in road networks. Then, based on DS index, this paper proposes a new prediction approach over data streams in road networks using Self-Adaptive Exponential Smoothing SAES.","PeriodicalId":113936,"journal":{"name":"Int. J. Knowl. Web Intell.","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A new spatio-temporal prediction approach based on aggregate queries\",\"authors\":\"Jun Feng, Zhonghua Zhu, Yaqing Shi, Liming Xu\",\"doi\":\"10.1504/IJKWI.2013.052723\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The prediction of spatio-temporal data streams which is based on aggregate queries has been an important research direction in the research field of databases. More and more methods have been proposed to obtain approximate aggregate results. However, they will consume a lot of time and storage space. This paper proposes Dynamic Sketch DS index by using modified method of Adaptive Multi-dimensional Histogram AMH* to intelligently partition static sketch which can improve the approximate quality of aggregate queries in road networks. Then, based on DS index, this paper proposes a new prediction approach over data streams in road networks using Self-Adaptive Exponential Smoothing SAES.\",\"PeriodicalId\":113936,\"journal\":{\"name\":\"Int. J. Knowl. Web Intell.\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-03-01\",\"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.2013.052723\",\"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.2013.052723","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new spatio-temporal prediction approach based on aggregate queries
The prediction of spatio-temporal data streams which is based on aggregate queries has been an important research direction in the research field of databases. More and more methods have been proposed to obtain approximate aggregate results. However, they will consume a lot of time and storage space. This paper proposes Dynamic Sketch DS index by using modified method of Adaptive Multi-dimensional Histogram AMH* to intelligently partition static sketch which can improve the approximate quality of aggregate queries in road networks. Then, based on DS index, this paper proposes a new prediction approach over data streams in road networks using Self-Adaptive Exponential Smoothing SAES.