Voxel modeling and association of ubiquitous spatiotemporal information in natural language texts
- Resource Type
- article
- Authors
- Dali Wang; Xiaochong Tong; Chenguang Dai; Congzhou Guo; Yi Lei; Chunping Qiu; He Li; Yuekun Sun
- Source
- International Journal of Digital Earth, Vol 16, Iss 1, Pp 868-890 (2023)
- Subject
- spatiotemporal voxels
ubiquitous spatiotemporal modeling
spatiotemporal association
discrete grid
Mathematical geography. Cartography
GA1-1776
- Language
- English
- ISSN
- 1753-8947
1753-8955
17538947
The ubiquitous spatiotemporal information extracted from Internet texts limits its application in spatiotemporal association and analysis due to its unstructured nature and uncertainty. This study uses ST-Voxel modeling to solve the problem of structured modeling and the association of ubiquitous spatiotemporal information in natural language texts. It provides a new solution for associating ubiquitous spatiotemporal information on the Internet and discovering public opinion. The main contributions of this paper include: (1) It proposes a convolved method for ST-Voxel, which solves the voxel modeling problem of unstructured and uncertain spatiotemporal objects and spatiotemporal relation in natural language texts. Experiments show that this method can effectively model 5 types of spatiotemporal objects and 16 types of uncertain spatiotemporal relation founded in texts; (2) It realizes the unknown event discovery based on voxelized spatiotemporal information association. Experiments show that this method can effectively solve the aggregation of ubiquitous spatiotemporal information in multi-natural language texts, which is conducive to discovering spatiotemporal events. The selection of convolution parameters in voxel modeling is also discussed. A parameter selection method for balancing the discovery capability and discovery accuracy of spatiotemporal events is given.