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LLM4POI
Dataset Summary
A preprocessed version of LLM4POI, including the FourSquare-NYC, Gowalla-CA, and FourSquare-TKY datasets. Please refer to their repository for more details.
LLM4POI frames next POI prediction task into a question-answering problem that is fed as prompt into a large language model (LLM). The model is trained to generate the next POI given the current trajectory and the historical trajectory. This repository hosts both the Q&A version and the raw txt and csv versions of the datasets.
This dataset is used to train GenUP models as described in our paper GenUP: Generative User Profilers as In-Context Learners for Next POI Recommender Systems.
Dataset Sources
Repository: neolifer/LLM4POI
Paper: Large Language Models for Next Point-of-Interest Recommendation
Repository: w11wo/GenUP
Paper: GenUP: Generative User Profilers as In-Context Learners for Next POI Recommender Systems
Dataset Structure
.
βββ README.md
βββ ca
β βββ preprocessed
β βββ test_qa_pairs_kqt.txt
β βββ train_qa_pairs_kqt.json
β βββ train_sample.csv
βββ nyc
β βββ preprocessed
β βββ test_qa_pairs_kqt.txt
β βββ train_qa_pairs_kqt.json
β βββ train_sample.csv
βββ tky
βββ preprocessed
βββ test_qa_pairs_kqt.txt
βββ train_qa_pairs_kqt.json
βββ train_sample.csv
Data Instances
An example of a line in test_qa_pairs_kqt.txt
:
<question>: The following data is a trajectory of user 2: At 2010-09-25 01:38:14, user 2 visited POI id 247 which is a Stadium and has Category id 261. At 2010-09-25 02:11:34, ... Given the data, At 2010-09-25 20:34:27, Which POI id will user 2 visit? Note that POI id is an integer in the range from 0 to 9690.<answer>: At 2010-09-25 20:34:27, user 2 will visit POI id 6350.
An example of a JSON object in train_qa_pairs_kqt.json
:
{
"question": "The following data is a trajectory of user 2: At 2010-09-25 01:38:14, user 2 visited POI id 247 which is a Stadium and has Category id 261. At 2010-09-25 02:11:34, ... Given the data, At 2010-09-25 20:34:27, Which POI id will user 2 visit? Note that POI id is an integer in the range from 0 to 9690.",
"answer": "At 2010-09-25 20:34:27, user 2 will visit POI id 6350."
}
An example of entries in train_sample.csv
:
check_ins_id,UTCTimeOffset,UTCTimeOffsetEpoch,pseudo_session_trajectory_id,UserId,Latitude,Longitude,PoiId,PoiCategoryId,PoiCategoryName
126094.0,2010-06-06 18:48:32,1275814112,0,1,37.6163560649,-122.3861503601,445,207,Airport
126278.0,2010-06-06 22:11:04,1275826264,0,1,37.7826046833,-122.4076080167,244,1,Coffee Shop
126314.0,2010-06-06 22:40:29,1275828029,0,1,37.7831295924,-122.4038743973,9346,121,Conference
126622.0,2010-06-07 06:01:04,1275854464,0,1,37.7815086,-122.4050282333,3253,128,Pub
Data Splits
train | test | |
---|---|---|
NYC | 11022 | 1447 |
CA | 36374 | 2864 |
TKY | 51661 | 7079 |
Additional Information
Citation
If you find this repository useful for your research, please consider citing our paper:
@misc{wongso2024genupgenerativeuserprofilers,
title={GenUP: Generative User Profilers as In-Context Learners for Next POI Recommender Systems},
author={Wilson Wongso and Hao Xue and Flora D. Salim},
year={2024},
eprint={2410.20643},
archivePrefix={arXiv},
primaryClass={cs.IR},
url={https://arxiv.org/abs/2410.20643},
}
@inproceedings{Li_2024, series={SIGIR 2024},
title={Large Language Models for Next Point-of-Interest Recommendation},
url={http://dx.doi.org/10.1145/3626772.3657840},
DOI={10.1145/3626772.3657840},
booktitle={Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval},
publisher={ACM},
author={Li, Peibo and de Rijke, Maarten and Xue, Hao and Ao, Shuang and Song, Yang and Salim, Flora D.},
year={2024},
month=jul, pages={1463β1472},
collection={SIGIR 2024}
}
Contact
If you have any questions or suggestions, feel free to contact Wilson at w.wongso(at)unsw(dot)edu(dot)au
.
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