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2021 | OriginalPaper | Chapter

8. Semantic Trajectories Data Models

Author : Maria Luisa Damiani

Published in: Handbook of Big Geospatial Data

Publisher: Springer International Publishing

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Abstract

Semantic trajectories is a major paradigm for the representation of movement data, complementary to spatial trajectories. In this article, we introduce key concepts, focusing in particular on the structural properties of semantic trajectories. Hence, we discuss a possible taxonomy of semantic trajectory models, based on their purpose.

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previous chapter Big Spatial Flow Data Analytics

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Alvares LO, Bogorny V, Kuijpers B, de Macedo J, Moelans B, Vaisman A (2007) A model for enriching trajectories with semantic geographical information. In: Proceedings of ACM GIS

Bogorny V, Renso C, de Aquino AR, de Siqueira FL, Alvares LO (2014) CONSTAnT – a conceptual data model for semantic trajectories of moving objects. Trans GIS 18(1):66–88CrossRef

Choi D-W, Pei J, Heinis T (2017) Efficient mining of regional movement patterns in semantic trajectories. Proc VLDB Endow 10(13):2073–2084CrossRef

Damiani ML, Güting RH (2014) Semantic trajectories and beyond. In: Proceedings of IEEE MDM

Damiani ML, Issa H, Güting RL, Valdés F (2015) Symbolic trajectories and application challenges. SIGSPATIAL Special 7(1):51–58CrossRef

Dey AK (2001) Understanding and using context. Pers Ubiquit Comput 5:4–7CrossRef

Giannotti F, Pedreschi D (2008) Mobility, data mining and privacy: geographic knowledge discovery, 1 edn. Springer Publishing Company, Incorporated, Berlin/HeidelbergCrossRef

Gryllakis F, Pelekis N, Doulkeridis C, Sideridis S, Theodoridis Y (2018) Spatio-temporal-keyword pattern queries over semantic trajectories with hermes@neo4j. In: Proceedings of EDBT

Güting RH, Böhlen MH, Erwig M, Jensen CS, Lorentzos NA, Schneider M, Vazirgiannis M (2000) A foundation for representing and querying moving objects. ACM Trans Database Syst 25:1–42CrossRef

Güting RH, Valdés F, Damiani ML (2015) Symbolic trajectories. ACM Trans Spat Algorithms Syst 1(2):7

Issa H, Damiani ML (2016) Efficient access to temporally overlaying spatial and textual trajectories. In: IEEE MDM

Kim Y, Han J, Yuan C (2015) Toptrac: topical trajectory pattern mining. In: Proceedings of KDD

Li X, Zhao K, Cong G, Jensen C, Wei W (2018) Deep representation learning for trajectory similarity computation. In: Proceedings of ICDE

Liu J, Wolfson O, Yin H (2006) Extracting semantic location from outdoor positioning systems. In: Proceedings of the 7th international conference on mobile data management, p 73

Mello RS, Bogorny V, Alvares LO, Zambom Santana L, Ferrero C, Frozza A, Schreiner GA, Renso C (2019) Master: a multiple aspect view on trajectories. Trans GIS 23(4):805–822

OGC (2019) Moving features encoding part 1: Xml core. http://docs.opengeospatial.org/is/18-075/18-075.html

Parent C, Spaccapietra S, Renso C, Andrienko G, Andrienko N, Bogorny V, Damiani ML, Gkoulalas-Divanis A, Macedo J, Pelekis N, Theodoridis Y, Yan Z (2013) Semantic trajectories modeling and analysis. ACM Comput Surv 45(4), Article 42, 32 pp

Spaccapietra S, Parent C, Damiani ML, de Macêdo JAF, Porto F, Vangenot C (2008) A conceptual view on trajectories. Data Knowl Eng 65(1):126–146CrossRef

Valdés F, Güting RH (2019) A framework for efficient multi-attribute movement data analysis. VLDB J 28(4):427–449CrossRef

Valdés F, Damiani ML, Güting RH (2013) Symbolic trajectories in secondo: pattern matching and rewriting. In: DASFAA

Xu J, Bao Z, Lu H (2019) Continuous range queries over multi-attribute trajectories,. In: IEEE international conference on data engineering (ICDE)

Yan Z, Chakraborty D, Parent C, Spaccapietra S, Aberer K (2013) Semantic trajectories: mobility data computation and annotation. ACM Trans Intell Syst Technol 4:1–38CrossRef

Zhang C, Han J, Shou L, Lu J, La Porta T (2014) Splitter: Mining fine-grained sequential patterns in semantic trajectories. Proc VLDB Endow 7(9):769–780CrossRef

Zheng Y (2015) Trajectory data mining: an overview. ACM Trans Intell Syst Technol 6(3):1–41CrossRef

Zheng Y, Zhou X (2011) Computing with spatial trajectories. Springer Publishing Company, Incorporated, New YorkCrossRef

Zheng Y, Wang L, Zhang R, Xie X, Ma W (2008) Geolife: managing and understanding your past life over maps. In: Proceedings of IEEE MDM

Zheng K, Zheng B, Xu J, Liu G, Liu A, Li Z (2016) Popularity-aware spatial keyword search on activity trajectories. World Wide Web 20(4):749–773CrossRef

Title: Semantic Trajectories Data Models
Author: Maria Luisa Damiani
Publisher: Springer International Publishing
Book: Handbook of Big Geospatial Data
Print ISBN: 978-3-030-55461-3

Electronic ISBN: 978-3-030-55462-0

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-55462-0_8

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