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- W4312979244 abstract "In this article, we propose a novel routine pattern extraction architecture to analyze the daily behaviors of mobile users. The key component of the proposed architecture is a dynamic programming-based sequence dissimilarity calculation method, which aims to measure the dissimilarity between trajectories and then extract patterns using the clustering method. The method exploits three different information: (1) spatial-temporal information, (2) information in the continuous same location in the sequence and (3) the probabilities of location occurrences in the data. We conduct experiments on a synthetic dataset and two real-world datasets. The obtained results demonstrate that our proposed method is efficient in extracting hidden routine patterns from users’ trajectory data." @default.
- W4312979244 created "2023-01-05" @default.
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- W4312979244 date "2022-01-01" @default.
- W4312979244 modified "2023-09-27" @default.
- W4312979244 title "Routine mining on location sequences" @default.
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- W4312979244 doi "https://doi.org/10.1016/j.procs.2022.09.231" @default.
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