Abstract
Spatio-temporal data management has progressed significantly towards efficient storage and indexing of mobility data. Typically such mobility data analytics is assumed to follow the model of a stream of (x,y,t) points, usually coming from GPS-enabled mobile devices. With large-scale adoption of GPS-driven systems in several application sectors (shipment tracking to geo-social networks), there is a growing demand from applications to understand the spatio-semantic behavior of mobile entities. Spatio-semantic behavior essentially means a semantic (and preferably contextual) abstraction of raw spatio-temporal location feeds. The core contribution of this paper lies in presenting a Hybrid Model and a Computing Platform for developing a semantic overlay - analyzing and transforming raw mobility data (GPS) to meaningful semantic abstractions, starting from raw feeds to semantic trajectories. Secondly, we analyze large-scale GPS data using our computing platform and present results of extracted spatio-semantic trajectories. This impacts a large class of mobile applications requiring such semantic abstractions over streaming location feeds in real systems today.
This work is supported by the Swiss FNRS grant 200021-116647/1.
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References
Alvares, L.O., Bogorny, V., Kuijpers, B., Macedo, J., Moelans, B., Vaisman, A.: A Model for Enriching Trajectories with Semantic Geographical Information. In: ACM-GIS, p. 22 (2007)
Banerjee, N., Chakraborty, D., Dasgupta, K., Mittal, S., Nagar, S., Saguna: R-U-In? - Exploiting Rich Presence and Converged Communications for Next-Generation Activity-Oriented Social Networking. In: MDM, pp. 222–231 (2009)
Frentzos, E.: Trajectory Data Management in Moving Object Databases. PhD thesis, University of Piraeus (2008)
Giannotti, F., Nanni, M., Pinelli, F., Pedreschi, D.: Trajectory Pattern Mining. In: KDD, pp. 330–339 (2007)
Giannotti, F., Pedreschi, D.: Mobility, Data Mining and Privacy - Geographic Knowledge Discovery. Springer, Heidelberg (2008)
Gómez, L., Vaisman, A.: Efficient Constraint Evaluation in Categorical Sequential Pattern Mining for Trajectory Databases. In: EDBT, pp. 541–552 (2009)
Güting, R., Schneider, M.: Moving Objects Databases. Morgan Kaufmann, San Francisco (2005)
Han, J., Lee, J.-G., Gonzalez, H., Li, X.: Mining Massive RFID, Trajectory, and Traffic Data Sets. In: KDD Tutorial (2008)
Jeung, H., Yiu, M.L., Zhou, X., Jensen, C.S., Shen, H.T.: Discovery of Convoys in Trajectory Databases. In: VLDB, pp. 1068–1080 (2008)
Lee, J.-G., Han, J., Li, X.: Trajectory Outlier Detection: A Partition-and-Detect Framework. In: ICDE, pp. 140–149 (2008)
Lee, J.-G., Han, J., Li, X., Gonzalez, H.: TraClass: Trajectory Classification Using Hierarchical Region-Based and Trajectory-Based Clustering. In: VLDB, pp. 1081–1094 (2008)
Lee, J.-G., Han, J., Whang, K.-Y.: Trajectory Clustering: a Partition-and-Group Framework. In: SIGMOD, pp. 593–604 (2007)
Mouza, C., Rigaux, P.: Mobility Patterns. GeoInformatica 9(4), 297–319 (2005)
Santer, R.D., Yamawaki, Y., Rind, F.C., Simmons, P.J.: Motor Activity and Trajectory Control During Escape Jumping in the Locust Locusta Migratoria. Journal of Comparative Physiology A 191(10), 965–975 (2005)
Schüssler, N., Axhausen, K.: Processing GPS Raw Data Without Additional Information. Transportation Research 8 (2009)
Spaccapietra, S., Parent, C., Damiani, M.L., de Macedo, J.A., Porto, F., Vangenot, C.: A Conceptual View on Trajectories. Data and Knowledge Engineering 65, 126–146 (2008)
Wessel, M., Luther, M., Möller, R.: What Happened to Bob? Semantic Data Mining of Context Histories. In: Description Logics (2009)
Wolfson, O., Xu, B., Chamberlain, S., Jiang, L.: Moving Objects Databases: Issues and Solutions. In: SSDBM, pp. 111–122 (1998)
Yan, Z., Macedo, J., Parent, C., Spaccapietra, S.: Trajectory Ontologies and Queries. Transactions in GIS 12(1), 75–91 (2008)
Zhang, J., Goodchild, M.F.: Uncertainty in Geographical Information, 1st edn. CRC, Boca Raton (2002)
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Yan, Z., Parent, C., Spaccapietra, S., Chakraborty, D. (2010). A Hybrid Model and Computing Platform for Spatio-semantic Trajectories. In: Aroyo, L., et al. The Semantic Web: Research and Applications. ESWC 2010. Lecture Notes in Computer Science, vol 6088. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13486-9_5
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DOI: https://doi.org/10.1007/978-3-642-13486-9_5
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