Hierarchical LSTM: Modeling Temporal Dynamics and Taxonomy in Location-Based Mobile Check-Ins

  • Chun-Hao LiuEmail author
  • Da-Cheng Juan
  • Xuan-An Tseng
  • Wei Wei
  • Yu-Ting Chen
  • Jia-Yu Pan
  • Shih-Chieh Chang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11440)


“Is there any pattern in location-based, mobile check-in activities?” “If yes, is it possible to accurately predict the intention of a user’s next check-in, given his/her check-in history?” To answer these questions, we study and analyze probably the largest mobile check-in datasets, containing 20 millions check-in activities from 0.4 million users. We provide two observations: “work-n-relax” and “diurnal-n-nocturnal” showing that the intentions of users’ check-ins are strongly associated with time. Furthermore, the category of each check-in venue, which reveals users’ intentions, has structure and forms taxonomy. In this paper, we propose Hierarchical LSTM that takes both (a) check-in time and (b) taxonomy structure of venues from check-in sequences into consideration, providing accurate predictions on the category of a user’s next check-in location. Hierarchical LSTM also projects each category into an embedding space, providing a new representation with stronger semantic meanings. Experimental results are poised to demonstrate the effectiveness of the proposed Hierarchical LSTM: (a) Hierarchical LSTM improves Accuracy@5 by 4.22% on average, and (b) Hierarchical LSTM learns a better taxonomy embedding for clustering categories, which improves Silhouette Coefficient by 1.5X.


Long Short-Term Memory Location-Based Social Network Point of Interest Behavior model 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Chun-Hao Liu
    • 1
    Email author
  • Da-Cheng Juan
    • 2
  • Xuan-An Tseng
    • 1
  • Wei Wei
    • 2
  • Yu-Ting Chen
    • 3
  • Jia-Yu Pan
    • 2
  • Shih-Chieh Chang
    • 1
    • 4
  1. 1.National Tsing Hua UniversityHsinchuTaiwan
  2. 2.Carnegie Mellon UniversityPittsburghUSA
  3. 3.University of California, Los AngelesLos AngelesUSA
  4. 4.Electronic and Optoelectronic System Research LaboratoriesITRIHsinchuTaiwan

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