Abstract
The interest in exploiting crowd-sourced location information has recently emerged as it can bring many valuable benefits. This is particularly the case where multi-dimensional semantic information represent human trajectories and contextual information arising in indoor and outdoor spaces. Users have different interests when interpreting and analysing trajectories. While some users just want to visualise the data, others require either higher-level information or aggregated knowledge. This paper introduces a modelling approach and data manipulation mechanisms that extract from generic semantic trajectories multiple views at different levels of abstraction to produce hybrid spatial representation for mobility patterns. This approach considers a multi-layered graph representation for trajectories according to some given spatio-temporal, contextual and user-defined criteria. The approach has been experimented with real data and implemented within a graph database that illustrates its potential.
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References
Alvares, L.O., Bogorny, V., Kuijpers, B., de Macedo, J.A.F., Moelans, B., Vaisman, A.: A model for enriching trajectories with semantic geographical information. In: Proceedings of the 15th Annual ACM International Symposium on Advances in Geographic Information Systems, pp. 1–8 (2007)
Bogorny, V., Renso, C., de Aquino, A.R., de Lucca Siqueira, F., Alvares, L.O.: Constant-a conceptual data model for semantic trajectories of moving objects. Trans. GIS 18(1), 66–88 (2014)
Cayèré, C., et al.: Multi-level and multiple aspect semantic trajectory model: application to the tourism domain. ISPRS Int. J. Geo-Inf. 10(9), 592 (2021)
Fileto, R., May, C., Renso, C., Pelekis, N., Klein, D., Theodoridis, Y.: The baquara2 knowledge-based framework for semantic enrichment and analysis of movement data. Data Knowl. Eng. 98, 104–122 (2015)
Gómez, L.I., Kuijpers, B., Vaisman, A.A.: Analytical queries on semantic trajectories using graph databases. Trans. GIS 23(5), 1078–1101 (2019)
Ilarri, S., Stojanovic, D., Ray, C.: Semantic management of moving objects: a vision towards smart mobility. Exp. Syst. Appl. 42(3), 1418–1435 (2015)
Izquierdo, Y.T., et al.: Stop-and-move sequence expressions over semantic trajectories. Int. J. Geog. Inf. Sci. 35(4), 793–818 (2021)
Jin, M., Claramunt, C.: A semantic model for human mobility in an urban region. J. Data Seman. 7(3), 171–187 (2018)
Kontarinis, A., Zeitouni, K., Marinica, C., Vodislav, D., Kotzinos, D.: Towards a semantic indoor trajectory model: application to museum visits. GeoInformatica 25(2), 311–352 (2021). https://doi.org/10.1007/s10707-020-00430-x
Li, H., Lu, H., Chen, X., Chen, G., Chen, K., Shou, L.: Vita: a versatile toolkit for generating indoor mobility data for real-world buildings. Proc. VLDB Endowment 9(13), 1453–1456 (2016)
Mello, R.D.S., et al.: Master: a multiple aspect view on trajectories. Trans. GIS 23(4), 805–822 (2019)
Noureddine, H., Ray, C., Claramunt, C.: Semantic trajectory modelling in indoor and outdoor spaces. In: 2020 21st IEEE International Conference on Mobile Data Management (MDM), pp. 131–136. IEEE (2020)
Noureddine, H., Ray, C., Claramunt, C.: A hierarchical indoor and outdoor model for semantic trajectories. Trans. GIS 26(1), 214–235 (2022). https://doi.org/10.1111/tgis.12841
Noureddine, H., Ray, C., Claramunt, C.: Multiple views of semantic trajectories in indoor and outdoor spaces. In: Proceedings of the 29th International Conference on Advances in Geographic Information Systems (2021)
Parent, C., et al.: Semantic trajectories modeling and analysis. ACM Comput. Surv. (CSUR) 45(4), 1–32 (2013)
Pelekis, N., Theodoridis, Y., Janssens, D.: On the management and analysis of our lifesteps. ACM SIGKDD Explor. Newsl. 15(1), 23–32 (2014)
Spaccapietra, S., Parent, C., Damiani, M.L., de Macedo, J.A., Porto, F., Vangenot, C.: A conceptual view on trajectories. Data Knowl. Eng. 65(1), 126–146 (2008)
Zheni, D., Frihida, A., Claramunt, C., Ben Ghezala, H.: A semantic-based data model for the manipulation of trajectories: application to urban transportation. In: Gensel, J., Tomko, M. (eds.) W2GIS 2015. LNCS, vol. 9080, pp. 124–142. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-18251-3_8
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Noureddine, H., Ray, C., Claramunt, C. (2022). Multiple Views Extraction from Semantic Trajectories. In: Karimipour, F., Storandt, S. (eds) Web and Wireless Geographical Information Systems. W2GIS 2022. Lecture Notes in Computer Science, vol 13238. Springer, Cham. https://doi.org/10.1007/978-3-031-06245-2_1
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DOI: https://doi.org/10.1007/978-3-031-06245-2_1
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