A new spatio–temporal prediction approach based on aggregate queries. (19th March 2013) - Feng, Jun; Zhu, Zhonghua; Shi, Yaqing; Xu, Liming
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).