GD-ML/IntTravel_dataset

IntTravel: A Real-World Dataset and Generative Framework for Integrated Multi-Task Travel Recommendation

Paper | GitHub

IntTravel is the first large-scale public dataset for integrated travel recommendation, including 4.1 billion interactions from 163 million users with 7.3 million POIs. Built upon this dataset, the authors introduce an end-to-end, decoder-only generative framework for multi-task recommendation. It incorporates information preservation, selection, and factorization to balance task collaboration with specialized differentiation.

Dataset Structure

The IntTravel dataset provides a comprehensive view of user journeys, including "when to depart", "how to travel", "where to go", and "what needs arise via the route".

Information of POIs

The dataset contains 7,291,872 POIs distributed across several major cities in China.

Field	Description
POI ID	A unique identifier for each Point of Interest.
Normalized score	A 0-1 score reflecting the overall popularity of the POI.
Geographic ID	Identifier for the POI's geographic block. Same GIDs indicate geographical proximity.
Category ID	A numerical identifier for the Point of Interest's category.
Administrative Region ID	The identifier for the administrative region of the POI.
Coordinates	The spatial coordinates of the POI on a 2D plane.

User Profiles

The dataset contains 162,815,861 users.

Field	Description
User ID	A unique identifier assigned to each user.
Profile Feature 1-6	Six profile features describing the user.

User Interactions

The dataset includes 4,129,827,011 user interaction events.

Field	Description
User ID	A unique identifier for the user who performed the interaction.
Timestamp	The time of the user interaction, recorded in milliseconds.
Action Type	A numerical ID representing the type of user behavior (e.g., click).
POI ID	The identifier of the Point of Interest involved in the interaction.
Geographic ID	The geographic block ID where the user was during the interaction.
Administrative Region ID	The administrative region ID where the user was during the interaction.
Weather	A numerical ID representing the weather condition during the interaction.
Travel Mode	A numerical ID for the user's chosen travel mode.
Via POI ID	The identifier for a way-point POI added by the user.

Citation

If you use this dataset in your research, please cite the following paper:

@article{yan2025inttravel,
  title={IntTravel: A Real-World Dataset and Generative Framework for Integrated Multi-Task Travel Recommendation},
  author={Huimin Yan and Longfei Xu and Junjie Sun and Zheng Liu and Wei Luo and Kaikui Liu and Xiangxiang Chu},
  journal={arXiv preprint arXiv:2602.11664},
  year={2025}
}