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From edit distance to augmented space-time-weighted edit distance: Detecting and clustering patterns of human activities in Puget Sound region

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  • Zhai, Wei
  • Bai, Xueyin
  • Peng, Zhong-ren
  • Gu, Chaolin

Abstract

Considering and measuring the similarity of human activities remains challenging. Existing studies of similarity measures based on traditional edit distance (ED), specifically on activity patterns, do not reflect the spatiotemporal characteristics in the measurement model. Additionally, interdependence between activities is ignored in existing multidimensional sequence alignment methods. To address the gap, we initially extend the traditional edit distance to a space-time-weighted edit distance (STW-ED). Specifically, differences in distance and time between activities are considered cost functions in the operation cost calculation (insertion, deletion, and substitution). We advance STW-ED to an augmented space-time-weighted edit distance method (ASTW-ED) that integrates an optimum-trajectory-based multidimensional sequence alignment method (OT-MDSAM) with STW-ED, treating the nonspatiotemporal dimensions as augment factors. In addition, ontology is considered for the similarity measure for nonspatiotemporal dimensions.

Suggested Citation

  • Zhai, Wei & Bai, Xueyin & Peng, Zhong-ren & Gu, Chaolin, 2019. "From edit distance to augmented space-time-weighted edit distance: Detecting and clustering patterns of human activities in Puget Sound region," Journal of Transport Geography, Elsevier, vol. 78(C), pages 41-55.
    • Handle: RePEc:eee:jotrge:v:78:y:2019:i:c:p:41-55
    DOI: 10.1016/j.jtrangeo.2019.05.003
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    References listed on IDEAS

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    1. Eric I. Pas, 1983. "A Flexible and Integrated Methodology for Analytical Classification of Daily Travel-Activity Behavior," Transportation Science, INFORMS, vol. 17(4), pages 405-429, November.
    2. Kay Axhausen & Andrea Zimmermann & Stefan Schönfelder & Guido Rindsfüser & Thomas Haupt, 2002. "Observing the rhythms of daily life: A six-week travel diary," Transportation, Springer, vol. 29(2), pages 95-124, May.
    3. E I Pas, 1984. "The Effect of Selected Sociodemographic Characteristics on Daily Travel-Activity Behavior," Environment and Planning A, , vol. 16(5), pages 571-581, May.
    4. P J Taylor & D N Parkes, 1975. "A Kantian View of the City: A Factorial-Ecology Experiment in Space and Time," Environment and Planning A, , vol. 7(6), pages 671-688, September.
    5. Christian Holz-Rau & Joachim Scheiner & Kathrin Sicks, 2014. "Travel Distances in Daily Travel and Long-Distance Travel: What Role is Played by Urban Form?," Environment and Planning A, , vol. 46(2), pages 488-507, February.
    6. Moshe Ben-Akiva & John L. Bowman, 1998. "Integration of an Activity-based Model System and a Residential Location Model," Urban Studies, Urban Studies Journal Limited, vol. 35(7), pages 1131-1153, June.
    7. W C Wilson, 1998. "Activity Pattern Analysis by Means of Sequence-Alignment Methods," Environment and Planning A, , vol. 30(6), pages 1017-1038, June.
    8. Marta C. González & César A. Hidalgo & Albert-László Barabási, 2009. "Understanding individual human mobility patterns," Nature, Nature, vol. 458(7235), pages 238-238, March.
    9. Schleith, Daniel & Widener, Michael & Kim, Changjoo, 2016. "An examination of the jobs-housing balance of different categories of workers across 26 metropolitan regions," Journal of Transport Geography, Elsevier, vol. 57(C), pages 145-160.
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    Cited by:

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