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--- |
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license: apache-2.0 |
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task_categories: |
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- other |
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tags: |
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- poi-recommendation |
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- trajectory-prediction |
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- human-mobility |
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dataset_info: |
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- config_name: default |
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features: |
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- name: user_id |
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dtype: string |
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- name: trail_id |
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dtype: string |
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|
- name: inputs |
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dtype: string |
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|
- name: targets |
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|
dtype: string |
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|
splits: |
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|
- name: train |
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|
num_bytes: 64771991 |
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|
num_examples: 151487 |
|
|
- name: validation |
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|
num_bytes: 9269946 |
|
|
num_examples: 21641 |
|
|
- name: test |
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|
num_bytes: 18507597 |
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num_examples: 43283 |
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download_size: 25240347 |
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dataset_size: 92549534 |
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- config_name: tabular |
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features: |
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- name: trail_id |
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dtype: string |
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- name: user_id |
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|
dtype: int64 |
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|
- name: venue_id |
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|
dtype: int64 |
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|
- name: latitude |
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|
dtype: float64 |
|
|
- name: longitude |
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|
dtype: float64 |
|
|
- name: name |
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|
dtype: string |
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|
- name: address |
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dtype: string |
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|
- name: venue_category |
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dtype: string |
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|
- name: venue_category_id |
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dtype: string |
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|
- name: venue_category_id_code |
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dtype: int64 |
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|
- name: venue_city |
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dtype: string |
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|
- name: venue_city_latitude |
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|
dtype: float64 |
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- name: venue_city_longitude |
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dtype: float64 |
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- name: venue_country |
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dtype: string |
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|
- name: timestamp |
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dtype: string |
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|
splits: |
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|
- name: train |
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|
num_bytes: 77227817 |
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|
num_examples: 380986 |
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|
- name: validation |
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|
num_bytes: 11070602 |
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|
num_examples: 54600 |
|
|
- name: test |
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|
num_bytes: 22046470 |
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num_examples: 108885 |
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|
download_size: 29874730 |
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dataset_size: 110344889 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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|
path: data/train-* |
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- split: validation |
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path: data/validation-* |
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- split: test |
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path: data/test-* |
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- config_name: tabular |
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data_files: |
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- split: train |
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path: tabular/train-* |
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- split: validation |
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path: tabular/validation-* |
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- split: test |
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path: tabular/test-* |
|
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--- |
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# Massive-STEPS-Istanbul |
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<div align="center"> |
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[](https://huggingface.co/collections/CRUISEResearchGroup/massive-steps-point-of-interest-check-in-dataset-682716f625d74c2569bc7a73) |
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[](https://huggingface.co/papers/2505.11239) |
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[](https://arxiv.org/abs/2505.11239) |
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[](https://github.com/cruiseresearchgroup/Massive-STEPS) |
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</div> |
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## Dataset Summary |
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**[Massive-STEPS](https://github.com/cruiseresearchgroup/Massive-STEPS)** is a large-scale dataset of semantic trajectories intended for understanding POI check-ins. The dataset is derived from the [Semantic Trails Dataset](https://github.com/D2KLab/semantic-trails) and [Foursquare Open Source Places](https://huggingface.co/datasets/foursquare/fsq-os-places), and includes check-in data from 15 cities across 10 countries. The dataset is designed to facilitate research in various domains, including trajectory prediction, POI recommendation, and urban modeling. Massive-STEPS emphasizes the importance of geographical diversity, scale, semantic richness, and reproducibility in trajectory datasets. |
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| **City** | **URL** | |
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| --------------- | :---------------------------------------------------------------------: | |
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| Bandung 🇮🇩 | [🤗](https://huggingface.co/datasets/CRUISEResearchGroup/Massive-STEPS-Bandung/) | |
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| Beijing 🇨🇳 | [🤗](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Beijing/) | |
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| Istanbul 🇹🇷 | [🤗](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Istanbul/) | |
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| Jakarta 🇮🇩 | [🤗](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Jakarta/) | |
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| Kuwait City 🇰🇼 | [🤗](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Kuwait-City/) | |
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| Melbourne 🇦🇺 | [🤗](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Melbourne/) | |
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| Moscow 🇷🇺 | [🤗](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Moscow/) | |
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| New York 🇺🇸 | [🤗](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-New-York/) | |
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| Palembang 🇮🇩 | [🤗](https://huggingface.co/datasets/CRUISEResearchGroup/Massive-STEPS-Palembang/) | |
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| Petaling Jaya 🇲🇾 | [🤗](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Petaling-Jaya/) | |
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| São Paulo 🇧🇷 | [🤗](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Sao-Paulo/) | |
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| Shanghai 🇨🇳 | [🤗](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Shanghai/) | |
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| Sydney 🇦🇺 | [🤗](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Sydney/) | |
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| Tangerang 🇮🇩 | [🤗](https://huggingface.co/datasets/CRUISEResearchGroup/Massive-STEPS-Tangerang/) | |
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| Tokyo 🇯🇵 | [🤗](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Tokyo/) | |
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### Dataset Sources |
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The dataset is derived from two sources: |
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1. **Semantic Trails Dataset**: |
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- Repository: [D2KLab/semantic-trails](https://github.com/D2KLab/semantic-trails) |
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- Paper: Monti, D., Palumbo, E., Rizzo, G., Troncy, R., Ehrhart, T., & Morisio, M. (2018). Semantic trails of city explorations: How do we live a city. *arXiv preprint [arXiv:1812.04367](https://arxiv.org/abs/1812.04367)*. |
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2. **Foursquare Open Source Places**: |
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- Repository: [foursquare/fsq-os-places](https://huggingface.co/datasets/foursquare/fsq-os-places) |
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- Documentation: [Foursquare Open Source Places](https://docs.foursquare.com/data-products/docs/access-fsq-os-places) |
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## Dataset Structure |
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```shell |
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. |
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├── istanbul_checkins_test.csv # test set check-ins |
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├── istanbul_checkins_train.csv # train set check-ins |
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├── istanbul_checkins_validation.csv # validation set check-ins |
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├── istanbul_checkins.csv # all check-ins |
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├── data # trajectory prompts |
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│  ├── test-00000-of-00001.parquet |
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│  ├── train-00000-of-00001.parquet |
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│  └── validation-00000-of-00001.parquet |
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└── README.md |
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``` |
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### Data Instances |
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An example of entries in `istanbul_checkins.csv`: |
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```csv |
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trail_id,user_id,venue_id,latitude,longitude,name,address,venue_category,venue_category_id,venue_category_id_code,venue_city,venue_city_latitude,venue_city_longitude,venue_country,timestamp |
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2013_1181,27,107,,,,,Bridge,4bf58dd8d48988d1df941735,244,Üsküdar,41.02274,29.01366,TR,2012-06-27 08:26:00 |
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2013_1181,27,1426,41.01087698106952,29.011255282139345,Harem Otogarı,Selimiye Mah. Üsküdar Sahil Yolu,Bus Station,4bf58dd8d48988d1fe931735,299,Üsküdar,41.02274,29.01366,TR,2012-06-27 09:14:00 |
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2013_1184,27,1035,,,,,Other Great Outdoors,4bf58dd8d48988d162941735,134,Üsküdar,41.02274,29.01366,TR,2012-07-12 07:42:00 |
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2013_1184,27,373,40.97029183099058,29.038406629399756,Happy Moon's,Fener Kalamış Cad. No: 89 Fenerbahçe,Restaurant,4bf58dd8d48988d1c4941735,220,Üsküdar,41.02274,29.01366,TR,2012-07-12 08:17:00 |
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2013_1185,27,9638,41.01004730321747,28.947255387140167,YusufpaÅŸa,,Outdoors & Recreation,4d4b7105d754a06377d81259,314,Istanbul,41.01384,28.94966,TR,2012-07-30 11:47:00 |
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``` |
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### Data Fields |
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| **Field** | **Description** | |
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| ------------------------ | ---------------------------------- | |
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| `trail_id` | Numeric identifier of trail | |
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| `user_id` | Numeric identifier of user | |
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| `venue_id` | Numeric identifier of POI venue | |
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| `latitude` | Latitude of POI venue | |
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| `longitude` | Longitude of POI venue | |
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| `name` | POI/business name | |
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| `address` | Street address of POI venue | |
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| `venue_category` | POI category name | |
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| `venue_category_id` | Foursquare Category ID | |
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| `venue_category_id_code` | Numeric identifier of category | |
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| `venue_city` | Administrative region name | |
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| `venue_city_latitude` | Latitude of administrative region | |
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| `venue_city_longitude` | Longitude of administrative region | |
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| `venue_country` | Country code | |
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| `timestamp` | Check-in timestamp | |
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### Dataset Statistics |
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| City | Users | Trails | POIs | Check-ins | #train | #val | #test | |
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| ----------- | :----: | :-----: | :---: | :-------: | :----: | :---: | :---: | |
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| Istanbul 🇹🇷 | 23,700 | 216,411 | 53,812 | 544,471 | 151,487 | 21,641 | 43,283 | |
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## Additional Information |
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### License |
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``` |
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Copyright 2024 Foursquare Labs, Inc. All rights reserved. |
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. |
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You may obtain a copy of the License at: http://www.apache.org/licenses/LICENSE-2.0 |
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
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See the License for the specific language governing permissions and limitations under the License. |
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``` |
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## 🔖 Citation |
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If you find this repository useful for your research, please consider citing our paper: |
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```bibtex |
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@misc{wongso2025massivestepsmassivesemantictrajectories, |
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title = {Massive-STEPS: Massive Semantic Trajectories for Understanding POI Check-ins -- Dataset and Benchmarks}, |
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author = {Wilson Wongso and Hao Xue and Flora D. Salim}, |
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year = {2025}, |
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eprint = {2505.11239}, |
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archiveprefix = {arXiv}, |
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primaryclass = {cs.LG}, |
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url = {https://arxiv.org/abs/2505.11239} |
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} |
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``` |
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### Contact |
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If you have any questions or suggestions, feel free to contact Wilson at `w.wongso(at)unsw(dot)edu(dot)au`. |
