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View all- Nayak SPandit D(2025)Daily activity-travel pattern identification using natural language processing and semantic matchingJournal of Transport Geography10.1016/j.jtrangeo.2024.104057122(104057)Online publication date: Jan-2025
Any human activity can be represented as a temporal sequence of actions performed to achieve a certain goal. Unlike machine-made time series, these action sequences are highly disparate as the time taken to finish a similar action might vary between ...
Changes in motion properties of trajectories provide useful cues for modeling and recognizing human activities. We associate an event with significant changes that are localized in time and space, and represent activities as a sequence of such events. ...
A large fraction of data generated via human activities such as online purchases, health records, spatial mobility, etc. can be represented as a sequence of events over a continuous-time. Learning deep learning models over these continuous-time event ...
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