Extracting Movement-based Topics for Analysis of Space Use

We present a novel approach to analyze spatio-temporal movement patterns using topic modeling. Our approach represents trajectories as sequences of place visits and moves, applies topic modeling separately to each collection of sequences, and synthesizes results. This supports the identification of dominant topics for both place visits and moves, the exploration of spatial and temporal patterns of movement, enabling understanding of space use. The approach is applied to two real-world data sets of car movements in Milan and UK road traffic, demonstrating the ability to uncover meaningful patterns and insights.

  • Published in:
    EuroVA: International Workshop on Visual Analytics
  • Type:
    Inproceedings
  • Authors:
    Andrienko, Gennady; Andrienko, Natalia; Hecker, Dirk
  • Year:
    2023

Citation information

Andrienko, Gennady; Andrienko, Natalia; Hecker, Dirk: Extracting Movement-based Topics for Analysis of Space Use, EuroVA: International Workshop on Visual Analytics, 2023, https://diglib.eg.org/handle/10.2312/eurova20231091, Andrienko.etal.2023b,

Associated Lamarr Researchers

lamarr institute person Andriyenko Gennadiy pi - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

Prof. Dr. Gennady Andrienko

Principal Investigator Human-centered AI Systems to the profile
lamarr institute person Andriyenko Nathaliya pi - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

Prof. Dr. Natalia Andrienko

Area Chair Human-centered AI Systems to the profile