Conference proceeding
Discovering interesting sub-paths in spatiotemporal datasets: a summary of results
Proceedings of the 19th ACM SIGSPATIAL International Conference on advances in geographic information systems, pp.44-53
GIS '11
11/01/2011
DOI: 10.1145/2093973.2093981
Abstract
Given a spatiotemporal (ST) dataset and a path in its embedding spatiotemporal framework, the goal is to to identify all interesting sub-paths defined by an interest measure. Sub-path discovery is of fundamental importance for understanding climate changes, agriculture, and many other application. However, this problem is computationally challenging due to the massive volume of data, the varying length of sub-paths and non-monotonicity of interestingness throughout a sub-path. Previous approaches find interesting unit sub-paths (e.g., unit time interval) or interesting points. By contrast, we propose a Sub-path Enumeration and Pruning (SEP) approach that finds collections of long interesting sub-paths. Two case studies using climate change datasets show that SEP can find long interesting sub-paths which represent abrupt climate change. We provide theoretical analyses of correctness, completeness and computational complexity of the proposed approach. We also provide experimental evaluation of two traversal strategies for enumerating and pruning candidate sub-paths.
Details
- Title: Subtitle
- Discovering interesting sub-paths in spatiotemporal datasets: a summary of results
- Creators
- Xun Zhou - University of MinnesotaShashi Shekhar - University of MinnesotaPradeep Mohan - University of MinnesotaStefan Liess - University of MinnesotaPeter Snyder - University of Minnesota
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of the 19th ACM SIGSPATIAL International Conference on advances in geographic information systems, pp.44-53
- Publisher
- ACM
- Series
- GIS '11
- DOI
- 10.1145/2093973.2093981
- Grant note
- DOI: 10.13039/100000145, name: Division of Information and Intelligent Systems, award: 1029711IIICXT IIS-0713214IGERT DGE-0504195CRI:IAD CNS-0708604; DOI: 10.13039/100000001, name: National Science Foundation, award: 1029711IIICXT IIS-0713214IGERT DGE-0504195CRI:IAD CNS-0708604; DOI: 10.13039/100000144, name: Division of Computer and Network Systems, award: 1029711IIICXT IIS-0713214IGERT DGE-0504195CRI:IAD CNS-0708604; DOI: 10.13039/100000082, name: Division of Graduate Education, award: 1029711IIICXT IIS-0713214IGERT DGE-0504195CRI:IAD CNS-0708604; DOI: 10.13039/100000005, name: U.S. Department of Defense, award: HM1582-08-1-0017HM1582-07-1-2035W9132V-09-C-0009
- Language
- English
- Date published
- 11/01/2011
- Academic Unit
- Business Analytics
- Record Identifier
- 9984380631502771
Metrics
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