Semantic-aware building and summarization of multiple aspect trajectories
Author:
Affiliation:
1. ISTI Institute of National Research Council, Pisa, Italy
2. Dept. of Computer Science, University of Pisa, Pisa, Italy
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3589132.3628363
Reference11 articles.
1. Review and classification of trajectory summarisation algorithms: From compression to segmentation
2. M. L. Damiani , F. Hachem , C. Quadri , M. Rossini , and S. Gaito . On location relevance and diversity in human mobility data. ACM Transactions on Spatial Algorithms and Systems (TSAS), 7(2):1--38 , 2020 . M. L. Damiani, F. Hachem, C. Quadri, M. Rossini, and S. Gaito. On location relevance and diversity in human mobility data. ACM Transactions on Spatial Algorithms and Systems (TSAS), 7(2):1--38, 2020.
3. The Baquara2 knowledge-based framework for semantic enrichment and analysis of movement data
4. Adaptive simplification of GPS trajectories with geographic context – a quadtree-based approach
5. A general methodology for building multiple aspect trajectories
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