A foundation for spatio-textual-temporal cube analytics
作者：
Highlights：
• We extend the standard cube model to add support for Spatial-Textual-Temporal (STT) data
• We also propose STT measures and a set of analytical operators (STTOLAP) over STT data
• We propose a pre-aggregation framework for the efficient computation of STT measures
• We compare STTCube’s query response time, storage cost, and accuracy with baseline methods
• Our comprehensive experimental evaluation shows that STTCube outperforms all the baseline methods
摘要
•We extend the standard cube model to add support for Spatial-Textual-Temporal (STT) data•We also propose STT measures and a set of analytical operators (STTOLAP) over STT data•We propose a pre-aggregation framework for the efficient computation of STT measures•We compare STTCube’s query response time, storage cost, and accuracy with baseline methods•Our comprehensive experimental evaluation shows that STTCube outperforms all the baseline methods
论文关键词：Data cube,OLAP,Spatial analytics,Textual analytics,Spatio-textual-temporal data,Spatial-textual-temporal measures
论文评审过程：Received 11 July 2021, Revised 21 November 2021, Accepted 14 February 2022, Available online 16 February 2022, Version of Record 12 May 2022.
论文官网地址：https://doi.org/10.1016/j.is.2022.102009
