Dr Martin Tomko

  • Room: Level: 03 Room: B304
  • Building: Engineering Block B
  • Campus: Parkville

Research interests

  • Geographic Information Retrieval (annotation, search and retrieval, and ranking of spatially related data)
  • Spatial analytics (mobility analytics, spatial machine learning and AI)
  • Spatial data integration (spatial databases, spatial data quality)
  • Spatial databases (autonomous data cleaning and integration)
  • Spatial information science (spatial communication, retail analytics, cyber-physical-social systems, spatial recommender systems)
  • Spatial infrastructures (eResearch infrastructure in the spatial domain)

Personal webpage

http://www.tomko.org

Biography

I am a Lecturer in the discipline of Geomatics with research interests in the area of Spatial Information Science, urban structure and network analysis, spatial databases and geographic information retrieval. My research thus contributes to numerous areas of spatial cognitive engineering.  I have a broad experience in design, implementation and management of the technical aspects of large-scale geospatial infrastructures and data handling, such as the design and implementation of a strategic Australian eResearch portal AURIN - The Australian Urban Research Infrastructure Network's flagship product.

Recent publications

  1. Tomko, M.; Winter, S. Beyond digital twins - A commentary. Environment and Planning B: Urban Analytics and City Science. SAGE PUBLICATIONS LTD. 2019, Vol. 46, Issue 2, pp. 395-399. DOI: 10.1177/2399808318816992
  2. Winter, S.; Majic, I.; Naghizade, E.; Tomko, M. Discovery of topological constraints on spatial object classes using an extended topological model. Journal of Spatial Information Science. University of Maine. 2019, Vol. 18, Issue 18, pp. 1-30. DOI: 10.5311/JOSIS.2019.18.459
  3. Winter, S.; Tomko, M.; Vasardani, M.; Richter, K-F.; Khoshelham, K.; Kalantari, M. Infrastructure-Independent Indoor Localization and Navigation. ACM Computing Surveys. Association for Computing Machinery (ACM). 2019, Vol. 52, Issue 3, pp. 1-24. DOI: 10.1145/3321516
  4. Tomko, M. Understanding indoor behavior: Where, what, with whom?. Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion. ACM Press. 2019, pp. 1455-1456. DOI: 10.1145/3041021.3051697
  5. Moss, R.; Naghizade, E.; Tomko, M.; Geard, N. What can urban mobility data reveal about the spatial distribution of infection in a single city?. BMC Public Health. BMC. 2019, Vol. 19, Issue 1. DOI: 10.1186/s12889-019-6968-x
  6. Adams, B.; Tomko, M. A critical look at cryptogovernance of the real world: Challenges for spatial representation and uncertainty on the blockchain. Leibniz International Proceedings in Informatics, LIPIcs. 2018, Vol. 114. DOI: 10.4230/LIPIcs.GIScience.2018.18
  7. Chen, H.; Vasardani, M.; Winter, S.; Tomko, M. A Graph Database Model for Knowledge Extracted from Place Descriptions. ISPRS International Journal of Geo-Information. MDPI AG. 2018, Vol. 7, Issue 6, pp. 1-30. DOI: 10.3390/ijgi7060221
  8. Chen, H.; Vasardani, M.; Winter, S.; Tomko, M. A Graph Database Model for Knowledge Extracted from Place Descriptions. ISPRS International Journal of Geo-Information. MDPI. 2018, Vol. 7, Issue 6. DOI: 10.3390/ijgi7060221
  9. Ren, Y.; Tomko, M.; Salim, FD.; Chan, J.; Clarke, CLA.; Sanderson, M. A Location-Query-Browse Graph for Contextual Recommendation. IEEE Transactions on Knowledge and Data Engineering. IEEE COMPUTER SOC. 2018, Vol. 30, Issue 2, pp. 204-218. DOI: 10.1109/TKDE.2017.2766059
  10. Wang, Y.; Winter, S.; Tomko, M. Collaborative activity-based ridesharing. Journal of Transport Geography. ELSEVIER SCI LTD. 2018, Vol. 72, pp. 131-138. DOI: 10.1016/j.jtrangeo.2018.08.013
  11. Naghizade, E.; Chan, J.; Ren, Y.; Tomko, M. Contextual Location Imputation for Confined WiFi Trajectories. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). SPRINGER INTERNATIONAL PUBLISHING AG. 2018, Vol. 10938, pp. 442-455. DOI: 10.1007/978-3-319-93037-4_35
  12. Hamzei, E.; Hua, H.; Tomko, M.; Chen, H.; Vasardani, M.; Winter, S. Deriving place graphs from spatial databases. CEUR Workshop Proceedings. 2018, Vol. 2087, pp. 25-32.
  13. Priyogi, B.; Sanderson, M.; Salim, F.; Chan, J.; Tomko, M.; Ren, Y. Identifying In-App User Actions from Mobile Web Logs. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). SPRINGER INTERNATIONAL PUBLISHING AG. 2018, Vol. 10938, pp. 300-311. DOI: 10.1007/978-3-319-93037-4_24
  14. Kaur, M.; Salim, FD.; Ren, Y.; Chan, J.; Tomko, M.; Sanderson, M. Shopping Intent Recognition and Location Prediction from Cyber-Physical Activities via Wi-Fi Logs. Proceedings of the 5th Conference on Systems for Built Environments - BuildSys '18. ASSOC COMPUTING MACHINERY. 2018, pp. 130-139. DOI: 10.1145/3276774.3276786
  15. Marshall, S.; Gil, J.; Kropf, K.; Tomko, M.; Figueiredo, L. Street Network Studies: from Networks to Models and their Representations. Networks and Spatial Economics. SPRINGER. 2018, Vol. 18, Issue 3, pp. 735-749. DOI: 10.1007/s11067-018-9427-9
  16. Scherrer, L.; Tomko, M.; Ranacher, P.; Weibel, R. Travelers or locals? Identifying meaningful sub-populations from human movement data in the absence of ground truth. EPJ Data Science. SPRINGEROPEN. 2018, Vol. 7, Issue 1. DOI: 10.1140/epjds/s13688-018-0147-7
  17. Ren, Y.; Tomko, M.; Salim, FD.; Chan, J.; Sanderson, M. Understanding the predictability of user demographics from cyber-physical-social behaviours in indoor retail spaces. EPJ Data Science. SPRINGEROPEN. 2018, Vol. 7, Issue 1. DOI: 10.1140/epjds/s13688-017-0128-2
  18. Ren, Y.; Tomko, M.; Salim, FD.; Ong, K.; Sanderson, M. Analyzing Web Behavior in Indoor Retail Spaces. Journal of the Association for Information Science and Technology. WILEY. 2017, Vol. 68, Issue 1, pp. 62-76. DOI: 10.1002/asi.23587
  19. Ren, Y.; Salim, FD.; Tomko, M.; Bai, YB.; Chan, J.; Qin, KK.; Sanderson, M. D-Log: A WiFi Log-based differential scheme for enhanced indoor localization with single RSSI source and infrequent sampling rate. Pervasive and Mobile Computing. ELSEVIER SCIENCE BV. 2017, Vol. 37, pp. 94-114. DOI: 10.1016/j.pmcj.2016.09.018
  20. Majic, I.; Winter, S.; Tomko, M. Finding equivalent keys in OpenStreetMap: Semantic similarity computation based on extensional definitions. Proceedings of the 1st Workshop on Artificial Intelligence and Deep Learning for Geographic Knowledge Discovery - GeoAI '17. ACM Press. 2017, pp. 24-32. DOI: 10.1145/3149808.3149813

View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile