@inproceedings{yamamoto-etal-2025-graph,
    title = "Graph-Structured Trajectory Extraction from Travelogues",
    author = "Yamamoto, Aitaro  and
      Otomo, Hiroyuki  and
      Ouchi, Hiroki  and
      Higashiyama, Shohei  and
      Teranishi, Hiroki  and
      Shindo, Hiroyuki  and
      Watanabe, Taro",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingestion-acl-25/2025.acl-long.690/",
    pages = "14116--14132",
    ISBN = "979-8-89176-251-0",
    abstract = "Human traveling trajectories play a central role in characterizing each travelogue, and automatic trajectory extraction from travelogues is highly desired for tourism services, such as travel planning and recommendation. This work addresses the extraction of human traveling trajectories from travelogues. Previous work treated each trajectory as a sequence of visited locations, although locations with different granularity levels, e.g., ``Kyoto City'' and ``Kyoto Station,'' should not be lined up in a sequence. In this work, we propose to represent the trajectory as a graph that can capture the hierarchy as well as the visiting order, and construct a benchmark dataset for the trajectory extraction. The experiments using this dataset show that even naive baseline systems can accurately predict visited locations and the visiting order between them, while it is more challenging to predict the hierarchical relations."
}