Mining spatiotemporal co-occurrence patterns in solar datasets
Abstract
We address the problem of mining spatiotemporal co-occurrence patterns (STCOPs) in solar datasets with extended polygon-based geometric representations. Specifically designed spatiotemporal indexing techniques are used in the mining of STCOPs. These include versions of two well-known spatiotemporal trajectory indexing techniques: the scalable and efficient trajectory index and Chebyshev polynomial indexing. We present a framework, STCOP-MINER, implementing a filter-and-refine STCOP mining algorithm, with the indexing techniques mentioned for efficiently performing data analysis.
- Publication:
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Astronomy and Computing
- Pub Date:
- November 2015
- DOI:
- 10.1016/j.ascom.2015.10.003
- Bibcode:
- 2015A&C....13..136A
- Keywords:
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- Spatiotemporal co-occurrence;
- Frequent pattern mining;
- Solar data mining;
- Spatiotemporal indexing