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Title	A Grid-Based And A Context-Oriented Trajectory Modeling For Mobility Prediction In Smart Cities
ID_Doc	2005
Authors	Boukhedouma H.; Meziane A.; Hammoudi S.; Benna A.
Year	2024
Published	Lecture Notes in Networks and Systems, 906 LNNS
DOI	http://dx.doi.org/10.1007/978-3-031-53824-7_14
Abstract	In the last decade, mobility prediction has played a crucial role in urban planning, traffic forecasting, advertising, and service recommendation. This paper addresses the prediction of mobility and emphasizes an essential step that is trajectory modeling (better the modelling is, better is the prediction). First, we propose a context-based and prediction-oriented trajectory model. Our model is based on a grid-oriented trajectory description technique that allows overcoming low precision and ambiguity issues. Second, our model is compared to some related trajectory models. Third, an application of the model in intelligent transportation domain is illustrated. Finally, to evaluate our model, we experiment it on a data mining-based prediction algorithm and show the results in terms of prediction accuracy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Author Keywords	context; mobility prediction; trajectory description and modeling; urban human mobility

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