--- license: apache-2.0 task_categories: - other tags: - poi-recommendation - trajectory-prediction - human-mobility dataset_info: - config_name: default features: - name: user_id dtype: string - name: trail_id dtype: string - name: inputs dtype: string - name: targets dtype: string splits: - name: train num_bytes: 173108 num_examples: 400 - name: validation num_bytes: 23979 num_examples: 58 - name: test num_bytes: 48202 num_examples: 115 download_size: 68457 dataset_size: 245289 - config_name: tabular features: - name: trail_id dtype: string - name: user_id dtype: int64 - name: venue_id dtype: int64 - name: latitude dtype: float64 - name: longitude dtype: float64 - name: name dtype: string - name: address dtype: string - name: venue_category dtype: string - name: venue_category_id dtype: string - name: venue_category_id_code dtype: int64 - name: venue_city dtype: string - name: venue_city_latitude dtype: float64 - name: venue_city_longitude dtype: float64 - name: venue_country dtype: string - name: timestamp dtype: string splits: - name: train num_bytes: 216345 num_examples: 1044 - name: validation num_bytes: 29763 num_examples: 141 - name: test num_bytes: 59608 num_examples: 285 download_size: 108969 dataset_size: 305716 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* - config_name: tabular data_files: - split: train path: tabular/train-* - split: validation path: tabular/validation-* - split: test path: tabular/test-* --- # Massive-STEPS-Beijing
[![huggingface](https://img.shields.io/badge/%F0%9F%A4%97-Hugging_Face_Collections-yellow)](https://huggingface.co/collections/CRUISEResearchGroup/massive-steps-point-of-interest-check-in-dataset-682716f625d74c2569bc7a73) [![huggingface](https://img.shields.io/badge/%F0%9F%A4%97-Hugging_Face_Papers-yellow)](https://huggingface.co/papers/2505.11239) [![arXiv](https://img.shields.io/badge/arXiv-2505.11239-b31b1b.svg)](https://arxiv.org/abs/2505.11239) [![GitHub](https://img.shields.io/badge/github-%23121011.svg?logo=github&logoColor=white)](https://github.com/cruiseresearchgroup/Massive-STEPS)
## Dataset Summary **[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. | **City** | **URL** | | --------------- | :---------------------------------------------------------------------: | | Bandung ๐Ÿ‡ฎ๐Ÿ‡ฉ | [๐Ÿค—](https://huggingface.co/datasets/CRUISEResearchGroup/Massive-STEPS-Bandung/) | | Beijing ๐Ÿ‡จ๐Ÿ‡ณ | [๐Ÿค—](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Beijing/) | | Istanbul ๐Ÿ‡น๐Ÿ‡ท | [๐Ÿค—](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Istanbul/) | | Jakarta ๐Ÿ‡ฎ๐Ÿ‡ฉ | [๐Ÿค—](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Jakarta/) | | Kuwait City ๐Ÿ‡ฐ๐Ÿ‡ผ | [๐Ÿค—](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Kuwait-City/) | | Melbourne ๐Ÿ‡ฆ๐Ÿ‡บ | [๐Ÿค—](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Melbourne/) | | Moscow ๐Ÿ‡ท๐Ÿ‡บ | [๐Ÿค—](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Moscow/) | | New York ๐Ÿ‡บ๐Ÿ‡ธ | [๐Ÿค—](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-New-York/) | | Palembang ๐Ÿ‡ฎ๐Ÿ‡ฉ | [๐Ÿค—](https://huggingface.co/datasets/CRUISEResearchGroup/Massive-STEPS-Palembang/) | | Petaling Jaya ๐Ÿ‡ฒ๐Ÿ‡พ | [๐Ÿค—](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Petaling-Jaya/) | | Sรฃo Paulo ๐Ÿ‡ง๐Ÿ‡ท | [๐Ÿค—](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Sao-Paulo/) | | Shanghai ๐Ÿ‡จ๐Ÿ‡ณ | [๐Ÿค—](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Shanghai/) | | Sydney ๐Ÿ‡ฆ๐Ÿ‡บ | [๐Ÿค—](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Sydney/) | | Tangerang ๐Ÿ‡ฎ๐Ÿ‡ฉ | [๐Ÿค—](https://huggingface.co/datasets/CRUISEResearchGroup/Massive-STEPS-Tangerang/) | | Tokyo ๐Ÿ‡ฏ๐Ÿ‡ต | [๐Ÿค—](https://huggingface.co/datasets/cruiseresearchgroup/Massive-STEPS-Tokyo/) | ### Dataset Sources The dataset is derived from two sources: 1. **Semantic Trails Dataset**: - Repository: [D2KLab/semantic-trails](https://github.com/D2KLab/semantic-trails) - 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)*. 2. **Foursquare Open Source Places**: - Repository: [foursquare/fsq-os-places](https://huggingface.co/datasets/foursquare/fsq-os-places) - Documentation: [Foursquare Open Source Places](https://docs.foursquare.com/data-products/docs/access-fsq-os-places) ## Dataset Structure ```shell . โ”œโ”€โ”€ beijing_checkins_test.csv # test set check-ins โ”œโ”€โ”€ beijing_checkins_train.csv # train set check-ins โ”œโ”€โ”€ beijing_checkins_validation.csv # validation set check-ins โ”œโ”€โ”€ beijing_checkins.csv # all check-ins โ”œโ”€โ”€ data # trajectory prompts โ”‚ย ย  โ”œโ”€โ”€ test-00000-of-00001.parquet โ”‚ย ย  โ”œโ”€โ”€ train-00000-of-00001.parquet โ”‚ย ย  โ””โ”€โ”€ validation-00000-of-00001.parquet โ””โ”€โ”€ README.md ``` ### Data Instances An example of entries in `beijing_checkins.csv`: ```csv 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 2013_113678,4328,161,39.98294814357289,116.49279095199559,Cafรฉ Flatwhite ไป™่‹ฑๅ’–ๅ•ก,"้…’ไป™ๆกฅ่ทฏ4ๅทๅคงๅฑฑๅญ่‰บๆœฏๅŒบ4 Dashanzi Art District, Jiuxianqiao Lu",Cafรฉ,4bf58dd8d48988d16d941735,87,Wangjing,39.9933,116.47284,CN,2012-04-08 04:55:00 2013_113678,4328,104,39.983048723481105,116.48867994097415,798 Art Zone,4 Jiuxianqiao Rd,Art Gallery,4bf58dd8d48988d1e2931735,137,Wangjing,39.9933,116.47284,CN,2012-04-08 04:58:00 2013_113678,4328,366,39.942338427744325,116.51860092630189,ๆœ้˜ณไฝ“่‚ฒๅฅ่บซไผ‘้—ฒๅ…ฌๅ›ญ,77 Yaojiayuan Rd,Other Great Outdoors,4bf58dd8d48988d162941735,81,Wangjing,39.9933,116.47284,CN,2012-04-08 07:01:00 2013_113680,4328,731,39.96069814865617,116.44995860089115,ๅฏฟๅธˆๅ‚… Sushifu,"Bldg 24, Yard 5A, Shuguang Xili",Japanese Restaurant,4bf58dd8d48988d111941735,17,Wangjing,39.9933,116.47284,CN,2012-04-16 11:51:00 2013_113680,4328,711,39.961040135069545,116.45046570746983,ๅ‡คๅ‡ฐๆฑ‡ Phoenix Galleria,"Bldg 24, Yard 5A, Shuguangxili",Shopping Mall,4bf58dd8d48988d1fd941735,162,Wangjing,39.9933,116.47284,CN,2012-04-16 12:26:00 ``` ### Data Fields | **Field** | **Description** | | ------------------------ | ---------------------------------- | | `trail_id` | Numeric identifier of trail | | `user_id` | Numeric identifier of user | | `venue_id` | Numeric identifier of POI venue | | `latitude` | Latitude of POI venue | | `longitude` | Longitude of POI venue | | `name` | POI/business name | | `address` | Street address of POI venue | | `venue_category` | POI category name | | `venue_category_id` | Foursquare Category ID | | `venue_category_id_code` | Numeric identifier of category | | `venue_city` | Administrative region name | | `venue_city_latitude` | Latitude of administrative region | | `venue_city_longitude` | Longitude of administrative region | | `venue_country` | Country code | | `timestamp` | Check-in timestamp | ### Dataset Statistics | City | Users | Trails | POIs | Check-ins | #train | #val | #test | | ----------- | :----: | :-----: | :---: | :-------: | :----: | :---: | :---: | | Beijing ๐Ÿ‡จ๐Ÿ‡ณ | 56 | 573 | 1,127 | 1,470 | 400 | 58 | 115 | ## Additional Information ### License ``` Copyright 2024 Foursquare Labs, Inc. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at: http://www.apache.org/licenses/LICENSE-2.0 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. See the License for the specific language governing permissions and limitations under the License. ``` ## ๐Ÿ”– Citation If you find this repository useful for your research, please consider citing our paper: ```bibtex @misc{wongso2025massivestepsmassivesemantictrajectories, title = {Massive-STEPS: Massive Semantic Trajectories for Understanding POI Check-ins -- Dataset and Benchmarks}, author = {Wilson Wongso and Hao Xue and Flora D. Salim}, year = {2025}, eprint = {2505.11239}, archiveprefix = {arXiv}, primaryclass = {cs.LG}, url = {https://arxiv.org/abs/2505.11239} } ``` ### Contact If you have any questions or suggestions, feel free to contact Wilson at `w.wongso(at)unsw(dot)edu(dot)au`.