Designing and Developing Spatial Experiences Ontology for Urban Rout Finding

Document Type : Persian Original Article

Authors

1 Geoinformation Technology Center of Excellence, Faculty of Geodesy & Geomatics Eng., K.N. Toosi University of Technology,

2 Geodesy and Geomatics Engineering, K.N. Toosi University, Mirdamad Ave. West, Tehran, Iran.

Abstract

Abstract- Spatial experience is the ability of comprehending relation between real world’s objects, spaces and areas and can be acquired after several years of learning and experience by the expert persons. This experience leads to generating spatial knowledge and can be helpful in making high accuracy, realistic and in accordance with reality decisions. Therefore, using some methods for storing and reusing this experiment and preventing the exit of experiences from organizations is necessary. In this research, different experience modeling methods such as semantic networks, rules, logic and ontology are investigated and due to the advantages of ontology method in comparison with other methods, this modeling method is chosen for proposing an algorithm for storing spatial experiences in urban route finding. In this regard, first, an ontology model is created with the taxi routes in Tehran city. Then, this ontology model is used for route finding and its results compared with Dikjestra’s algorithm at peak traffic times. The results show that although the route lengths of ontology based route finding algorithm are longer than route lengths of Dikjestra’s algorithm but its travel times are lower and in some routes the difference between travel times reaches to 10 minutes.

Keywords

References

[1] B., Kamsu-Foguem, and F.H., Abanda, “Experience modeling with graphs encoded knowledge for construction industry”, Computers in Industry, 70, pp.79-88, 2015.
[2] M.H., Abel,  “Knowledge map-based web platform to facilitate organizational learning return of experiences”, Computers in Human Behavior, 51, pp.960-966, 2015.
[3] D., Mourtzis, M., Doukas, and C., Giannoulis, “An Inference-based Knowledge Reuse Framework for Historical Product and Production Information Retrieval”, Procedia CIRP, 41, pp.472-477, 2016.
[4]P.P., Ruiz, B.K., Foguem, and B., Grabot, “Generating knowledge in maintenance from Experience Feedback. Knowledge-Based Systems”, 68, pp.4-20, 2014.
[5] W.L., Mikos, J.C.,  Ferreira, P.E., Botura, and L.S., Freitas, “A system for distributed sharing and reuse of design and manufacturing knowledge in the PFMEA domain using a description logics-based ontology”, Journal of Manufacturing Systems, 30(3), pp.133-143, 2011.
[6] K., Efthymiou, K., Sipsas, D., Mourtzis, and G., Chryssolouris, “On knowledge reuse for manufacturing systems design and planning: A semantic technology approach”, CIRP Journal of Manufacturing Science and Technology, 8, pp.1-11, 2015.
[7] S., Moehrle, and W., Raskob, “Structuring and reusing knowledge from historical events for supporting nuclear emergency and remediation management”, Engineering Applications of Artificial Intelligence, 46, pp.303-311, 2015.
[8] B.K., Foguem, T., Coudert, C. Béler, and L., Geneste, “Knowledge formalization in experience feedback processes: An ontology-based approach”, Computers in Industry, 59(7), pp.694-710, 2008.
[9] R.S., Renu, and G., Mocko, “Computing similarity of text-based assembly processes for knowledge retrieval and reuse”, Journal of Manufacturing Systems, 39, pp.101-110, 2016.
[10] E.R., Reyes, S., Negny, G.C. Robles, and J.M., Le Lann, “Improvement of online adaptation knowledge acquisition and reuse in case-based reasoning: Application to process engineering design”, Engineering Applications of Artificial Intelligence, 41, pp.1-16, 2015.
[11] Y., Hu, K., Janowicz, D., Carral, S., Scheider, W., Kuhn, G., Berg-Cross, P., Hitzler, M. Dean, and D., Kolas, September. “A geo-ontology design pattern for semantic trajectories”, In International Conference on Spatial Information Theory, pp. 438-456. Springer International Publishing, 2013.
[12] M., Effati, and A., Sadeghi Niaraki, “A semantic based classification and regression tree approach for modelling complex spatial rules in motor vehicle crashes domain”, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 5(4), pp.181-194,2015.
[13] M., Baglioni, J., Macedo, C., Renso, and M., Wachowicz, “An ontology-based approach for the semantic modelling and reasoning on trajectories”, In International Conference on Conceptual Modeling, pp. 344-353, Springer Berlin Heidelberg, 2008.
[14] U., Durak, H., OǦUZTÜZÜN, and S.K., Ider, “Ontology-based domain engineering for trajectory simulation reuse”, International Journal of Software Engineering and Knowledge Engineering, vol. 19(08), pp.1109-1129, 2009.
[15] E., Camossi, P. Villa, and L., Mazzola, “Semantic-based anomalous pattern discovery in moving object trajectories”, arXiv preprint arXiv:1305.1946, 2013.
[16] R., Wannous, J., Malki, A., Bouju, and C., Vincent, “Modelling mobile object activities based on trajectory ontology rules considering spatial relationship rules”, In Modeling approaches and algorithms for advanced computer applications, pp. 249-258, Springer International Publishing, 2013.
[17] T., Malgundkar, M.Rao, and S.S., Mantha, “GIS driven urban traffic analysis based on ontology”, International Journal of Managing Information Technology, vol. 4(1), pp.15, 2012.
[18] A., Sadeghi-Niaraki, A., Rajabifard, K., Kim, and J., Seo, “Ontology based SDI to facilitate spatially enabled society”, In Proceedings of GSDI 12 World Conference, pp. 19-22, 2010.
[19] A.S. Niaraki, and K., Kim, “Ontology based personalized route planning system using a multi-criteria decision making approach”, Expert Systems with Applications, vol. 36(2), pp.2250-2259, 2009.
[20] S., Saeedi, N., El-Sheimy, M. Malek, and N., Samani, “June. An ontology based context modeling approach for mobile touring and navigation system”, In Proceedings of the The 2010 Canadian Geomatics Conference and Symposium of Commission I, ISPRS Convergence in Geomatics–Shaping Canada’s Competitive Landscape, Calgary, Canada, pp. 15-18, 2010.
[21] G.S., Stephan, H.S., Pascal, and A.S., Andreas, “Knowledge representation and ontologies”, Springer Berlin Heidelberg, pp. 51-105, 2007.
[22] J.F., Sowa, “Knowledge representation: logical, philosophical, and computational foundations”, Pacific Grove: Brooks/Cole, vol. 13, 2000.
[23] J.W., Lloyd, “Foundations of logic programming”, Springer Science & Business Media, 2012. .
[24] J., Minker, “Logic and Databases Past, Present, and Future”, AI Magazine, vol. 18(3), pp. 21, 1997.
[25] T.R., Gruber, “A Translation Approach to Portable Ontology Specification”, Knowledge Acquisition, vol. 5, pp. 199-220, 1993.
[26] C., Roussey, F., Pinet, M.A., Kang, and O., Corcho, “An introduction to ontologies and ontology engineering”, In Ontologies in Urban Development Projects, pp. 9-38. Springer London, 2011.
[27] M.A., Musen, “Dimensions of knowledge sharing and reuse”, Computers and Biomedical Research, vol. 25, pp.435-467, 1992.
[28] N.F., Noy, and D.L., McGuinness, “Ontology development 101: A guide to creating your first ontology”, 2001.
[29] D.L., McGuinness, and J., Wright, “Conceptual Modeling for Configuration: A Description Logic-based Approach”, Artificial Intelligence for Engineering Design, Analysis, and Manufacturing - special issue on Configuration, 1998.
[30] D.L., McGuinness, R., Fikes, J., Rice, and S., Wilder, “An Environment for Merging and Testing Large Ontologies”, Principles of Knowledge Representation and Reasoning: Proceedings of the Seventh International Conference (KR2000). A. G. Cohn, F. Giunchiglia and B. Selman, editors. San Francisco, CA, Morgan Kaufmann Publishers, 2000.
[31] P., Lee, “What's Wrong with Logic Models”, LCSA: Occasional Paper, (1), 2011.
[32] Q., Ni, I., Pau de la Cruz, and A.B., García Hernando, “A foundational ontology-based model for human activity representation in smart homes”, Journal of Ambient Intelligence and Smart Environments, vol. 8(1), pp.47-61, 2016.
[33] B., Smith, “Logic and formal ontology”, In Husserl's Phenomenology: A Textbook,pp. 29-67. Lanham: University Press of America, 1989.
[34] A., Gomez-Perez, “Some ideas and examples to evaluate ontologies”, Knowledge Systems Laboratory, Stanford University, 1994.
[35] A., Gomez-Perez, “Towards a framework to verify knowledge sharing technology”, Expert Systems with Applications, vol.11, no.4, pp.519–529, 1996.
[36] J., Brank, M., Grobelnik, and D., Mladenic, “A survey of ontology evaluation techniques”, Proc. Conf. on Data Mining and Data Warehouses, Ljubljana, Slovenia, 2005.
[37] R., Porzel, and R. Malaka, “A task-based approach for ontology evaluation”, ECAI 2004 Workshop Ont. Learning and Population, 2004.
[38] C., Brewster, H., Alani, S., Dasmahapatra, and Y., Wilks, “Data driven ontology evaluation”, Proceedings of Int. Conf. on Language Resources and Evaluation, Lisbon, pp.641-644, 2004..
[39] A., Lozano-Tello, and A., Gomez-Perez, “Ontometric: a method to choose the appropriate ontology”, Journal of database management, vol.15, no.2, pp.1-18, 2004.
Journal of Soft Computing and Information Technology
Volume 7, Issue 2 - Serial Number 2
Fall & Winter
January 2019
Pages 1-15

Files

Share

How to cite

Statistics