@inproceedings{c4370d57ae44467da582accc3c4e12c5,
title = "Refinement and Trust Modeling of Spatio-Temporal Big Data",
abstract = "The conventional studies of spatio-temporal data models and their big data applications cannot reliably reflect the large volume, heterogeneity and dynamics of spatio-temporal big data. In this paper, the structure and function expression of spatio-temporal metadata is analyzed. With fused and normalized spatio-temporal reference and data structure, the constraint rules of spatio-temporal big data refinement are proposed. Using the domain specific modeling (DSM) and the data granulation algorithms, an object-oriented modeling language, the thrust modeling of spatio-temporal big data, and the aggregated status correlation of unified model data are established. This work utilizes the trust modeling theory and the spatio-temporal data processing methods and defines a case study that converts spatio-temporal data into dynamic complex big data. This research paves the way for the trust modeling and validation of spatio-temporal big data.",
keywords = "Domain specific modeling, Granulation, Refinement, Spatio-temporal big data, Trust modeling",
author = "Lei Zhang",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; Computing Conference, 2019 ; Conference date: 16-07-2019 Through 17-07-2019",
year = "2019",
doi = "10.1007/978-3-030-22868-2\_10",
language = "英语",
isbn = "9783030228675",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "132--144",
editor = "Kohei Arai and Rahul Bhatia and Supriya Kapoor",
booktitle = "Intelligent Computing - Proceedings of the 2019 Computing Conference",
address = "德国",
}