A framework for mining lifestyle profiles through multi-dimensional and high-order mobility feature clustering Article Swipe

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Yeshuo Shu , Gangcheng Zhang , Keyi Liu , Jintong Tang , Liyan Xu ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2312.00411

Human mobility demonstrates a high degree of regularity, which facilitates the discovery of lifestyle profiles. Existing research has yet to fully utilize the regularities embedded in high-order features extracted from human mobility records in such profiling. This study proposes a progressive feature extraction strategy that mines high-order mobility features from users' moving trajectory records from the spatial, temporal, and semantic dimensions. Specific features are extracted such as travel motifs, rhythms decomposed by discrete Fourier transform (DFT) of mobility time series, and vectorized place semantics by word2vec, respectively to the three dimensions, and they are further clustered to reveal the users' lifestyle characteristics. An experiment using a trajectory dataset of over 500k users in Shenzhen, China yields seven user clusters with different lifestyle profiles that can be well interpreted by common sense. The results suggest the possibility of fine-grained user profiling through cross-order trajectory feature engineering and clustering.

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Profiling (computer programming) Cluster analysis Computer science Data mining Word2vec Trajectory Feature extraction Artificial intelligence Physics Operating system Embedding Astronomy

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2312.00411
PDF: https://arxiv.org/pdf/2312.00411
OA Status: green
Related Works: 10
OpenAlex ID: https://openalex.org/W4389325872

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DOI: https://doi.org/10.48550/arxiv.2312.00411

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Title: A framework for mining lifestyle profiles through multi-dimensional and high-order mobility feature clustering

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Language: en

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Publication year: 2023

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Publication date: 2023-12-01

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Authors: Yeshuo Shu, Gangcheng Zhang, Keyi Liu, Jintong Tang, Liyan Xu

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Landing page: https://arxiv.org/abs/2312.00411

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Concepts: Profiling (computer programming), Cluster analysis, Computer science, Data mining, Word2vec, Trajectory, Feature extraction, Artificial intelligence, Physics, Operating system, Embedding, Astronomy

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