COhave research

Social Pattern Discovery for GPS Datasets

This work introduces a method to analyze human mobility and social interactions, highlighting the use of geohash codes for spatial clustering and the identification of social encounters with and without time constraints. Our approach uncovers "followers" by tracking how people move to subsequent geohashes within a specific time interval, revealing patterns of coordinated mobility. Our analysis includes the construction of a social graph visualizing individual connections.

The Geolife GPS dataset, which comprises 17,621 trajectories covering approximately 1.2 million kilometers and spans over 48,000 hours across five years. Our approach, adaptable to various GPS datasets, converts movement trajectories into a series of geohash codes, enhancing the analysis of social behaviors and connections. Remarkably, despite the dataset's size, our analysis, effectively reduces these complex interactions into a simplified representation consisting of only 96 nodes and 131 edges. This reduction to a manageable network graph underscores our method's efficiency in capturing the essence of social connections within such a large dataset.

Maroš Čavojský. Social Pattern Discovery for GPS Datasets. 28th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES) 2024, tba.

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User Experience in GPS Trajectory Search using Pattern

We have proposed, implemented and compared several approaches for user movement (trajectory) extraction. Unlike other approaches, our approaches are purely based on WiFi sensing without the knowledge of user's physical location. This is a favorable approach in scenarios that aim at high energy efficiency. We only collect WiFi information passively, i.e. we only listen to broadcast beacons and do not transmit any probe requests.

Maroš Čavojský, Martin Drozda. User Experience Meets GPS Trajectory Search. IEEE International Conference on Systems, Man, and Cybernetics (SMC) 2023 Maroš Čavojský, Martin Drozda. Search by Pattern in GPS Trajectories. EAI MobiCASE 2022, 13th EAI International Conference on Mobile Computing, Applications and Services. Springer Nature Switzerland, 2022. p. 117-132.

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Comparison of GPS Trajectories with the Needleman-Wunsch Algorithm

Our goal was to test if the Needleman-Wunsch algorithm (NWA) for sequence alignment can be efficiently applied to comparing user trajectories, where user locations are provided by Global positioning system (GPS). We proposed several adjustments to this algorithm. Our results show that NWA can be successfully applied to user trajectory comparison.

Maroš Čavojský, Martin Drozda, Zoltán Balogh. Analysis and Experimental Evaluation of the Needleman-Wunsch Algorithm for Trajectory Comparison. Expert Systems with Applications, 2020, Elsevier. Maroš Čavojský, Martin Drozda. Comparison of User Trajectories with the Needleman-Wunsch Algorithm. MobiCASE 2019, 10th EAI International Conference on Mobile Computing, Applications and Services. Springer, Cham. 2019. p. 141-154.

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