Abstract
The increasing adoption of social network applications has been an important source of information nowadays. The analysis of human behaviors in social networks has been brought to the forefront of several studies. Location-Based Social Networks (LBSN) are one of the possible means that allow the prediction of human behaviors through the efficient analysis of user’s mobility patterns. Despite the remarkable progress in this research direction, however, LBSN is still hindered by the lack of literature defining the semantic aspects of the user’s mobility. This research presents a contribution to the latest knowledge representation languages and Semantic Web technologies. We focus on studying human behavior mobility which is the core in location recommendation systems. Bringing to the ridesharing context, an ontology model with its underlying description logics to efficiently annotate human mobility is presented. Finally, experimental results, performed on two location-based social networks, namely, Brightkite (https://snap.stanford.edu/data), and BlaBlaCar (https://www.blablacar.co.uk/) are presented.
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Notes
- 1.
Following SROIQ description logic notations introduced in [22].
References
Schreieck, M., Safetli, H., Siddiqui, S., Pflugler, C., Wiesche, M., Krcmar, H.: A matching algorithm for dynamic ridesharing. Transp. Res. Procedia 272–285 (2016)
Gruber, T.R.: A translation approach to portable ontology specifications. Knowl. Acquis. 5(2), 199–220 (1993). (Special Issue: Current Issues in Knowledge Modeling Archive. Academic Press Ltd., London, UK)
Cho, E., Myers, S.A., Leskovec, J.: Friendship and mobility, user movement in location-based social networks. In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, CA, USA, 21–24 Aug 2011, pp. 1082–1090
Sarwat, M., Bao, J., Eldawy, A., Levandoski, J.J., Magdy, A., Mokbel, M.F.: Sindbad: a location-based social networking system. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2012, Scottsdale, AZ, USA, 20–24 May 2012, pp. 649–652
Sasikumar, C., Jaganathan, S.: A dynamic carpooling system with social network based filtering. Res. J. Eng. 8(3), 263–267 (2017)
Aissaoui, R., Houssaini, O.I.: CARPOOLING APPLICATION? KwiGo, Available via http://www.aui.ma/ssecapstone-repository/pdf/CARPOOLING-APPLICATION-KwiGo.pdf, Apr 2015
Yan, S., Chen, C.Y.: A model and a solution algorithm for the carpooling problem with pre-matching information. Comput. Ind. Eng. 61(3), 512–524 (2011)
Yan, S., Chen, C.Y., Chang, S.C.: A carpooling model and solution method with stochastic vehicle travel times. IEEE Trans. Intell. Transp. Syst. 15(1), 7–61 (2014)
Nagare, D.B., More, K.L., Tanwar, N.S., Kulkarni, S., Gunda, K.C.: Dynamic car-pooling application development on android platform. Int. J. Innov. Technol. Explor. Eng. (2013)
Parent, C., Spaccapietra, S., Renso, C., Andrienko, G., Andrienko, N., Bogorny, V., Damiani, M.L., Gkoulalas-Divanis, A., Macedo, J., Pelekis, N., Theodoridis, Y., Yan, Z.: Semantic trajectories modeling and analysis. ACM Comput. Surv. 45(4), 42:1–42:32 (2013)
Fileto, R., Krüger, M., Pelekis, N., Theodoridis, Y., Renso, C.: Baquara: a holistic ontological framework for movement analysis using linked data. In: 32nd International Conference on Conceptual Modeling, Hong-Kong, China, 11–13 Nov 2013, pp. 342–355
Damiani, M.L., Güting, R.H., Valdés, F., Issa, H.: Moving objects beyond raw and semantic trajectories. In: Proceedings of the 3rd International Workshop on Information Management for Mobile Applications, Riva del Garda, Italy, 26 Aug 2013, p. 4
Ya, Z., Chakraborty, D., Parent, C., Spaccapietra, S., Aberer, K.L.: Semantic trajectories: mobility data computation and annotation. ACM TIST 4(3), 49 (2013)
Bogorny, V., Renso, C., Ribeiro de Aquino, A., Siqueira, F.D.L., Alvares, L.O.: CONSTAnT—a conceptual data model for semantic trajectories of moving objects. Trans. GIS (2013)
Zheng, K., Shang, S., Yuan, N.J., Yang, Y.: Towards efficient search for activity trajectories. In: 29th IEEE International Conference on Data Engineering, Brisbane, Australia, 8–12 Apr 2013, pp. 230–241
Renso, C., Baglioni, M., Fernandes de Macêdo, J.A., Trasarti, R., Wachowicz, M.: How you move reveals who you are: understanding human behavior by analyzing trajectory data. Knowl. Inf. Syst. 37(2), 331–362 (2013)
Carral, D., Scheider, S., Janowicz, K., Vardeman, C., Krisnadhi, A.A., Hitzler, P.: An ontology design pattern for cartographic map scaling. In: 10th International Conference on The Semantic Web: Semantics and Big Data, Montpellier, France, 26–30 May 2013, pp. 76–93
Martínez, D.C., Janowicz, K., Hitzler, P.: A logical geo-ontology design pattern for quantifying over types. In: SIGSPATIAL 2012 International Conference on Advances in Geo-graphic Information Systems (formerly known as GIS), Redondo Beach, CA, USA, 7–9 Nov 2012, pp. 239–248
Hu, Y., Janowicz, K., Carral, D., Scheider, S., Kuhn, W., Berg-Cross, G., Hitzler, P., Dean, M., Kolas, D.: A geo-ontology design pattern for semantic trajectories. In: 11th International Conference on Spatial Information Theory, Scarborough, UK, 2–6 September 2013, pp. 438–456
Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F.: The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press, Cambridge (2003)
Baader, F., Sattler, U.: An overview of tableau algorithms for description logics. Stud. Logica 69(1), 5–40 (2011)
Horrocks, I., Kutz, O., Sattler, U.: The even more irresistible SROIQ, pp. 57–67
The Protégé website, Available via http://protege.stanford.edu
Sirin, E., Parsia, B.: SPARQL-DL: SPARQL Query for OWL-DL, In 3rd OWL Experiences and Directions Workshop (OWLED) (2007)
Kollia, I., Glimm, B., Horrocks, I.: SPARQL query answering over OWL ontologies. In: Proceedings of the 8th Extended Semantic Web Conference on The Semantic Web: Research and Applications, Heraklion, Crete, Greece, 2011, pp. 382–396
Archdeacon, T.J.: Correlation and Regression Analysis: A Historian’s Guide. University of Wisconsin Press, Madison (1994)
Wagih, H.M., Mokhtar, H.M.O., Ghoniemy, S.S.: SIMBA: a semantic-influence measurement based algorithm for detecting influential diffusion in social networks. In: The 13th IEEE International Conference on Semantic Computing, 2019, pp. 178–182
Wagih, H.M., Mokhtar, H.M.O.: HBTOnto: an ontology model for analyzing human behavior trajectories. In: 11th International Conference on Semantics, Knowledge and Grids (SKG), 2015, pp. 126–132
Acknowledgements
This research is an extension to the previously published paper [28] in the 11th International Conference on Semantics, Knowledge and Grids (SKG) conference in 2015.
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Wagih, H.M., Mokhtar, H.M.O. (2021). Ridology: An Ontology Model for Exploring Human Behavior Trajectories in Ridesharing Applications. In: Al-Emran, M., Shaalan, K., Hassanien, A. (eds) Recent Advances in Intelligent Systems and Smart Applications. Studies in Systems, Decision and Control, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-47411-9_30
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