FGRec: A Fine-Grained Point-of-Interest Recommendation Framework by Capturing Intrinsic Influences (IJCNN 2020)
Details for Precision:
| Dataset | Precision@5 | Precision@10 | Precision@20 | Precision@50 |
| ---------- | ------------| -------------| ---------------| -------------|
| Foursquare | 0.04712 | 0.03772 | 0.02885 | 0.0204 |
| Yelp | 0.030783 | 0.0258491 | 0.0214022 | 0.015348 |
Details for Recall:
| Dataset | Recall@5 | Recall@10 | Recall@20 | Recall@50 |
| ---------- | ------------| -------------| ---------------| -------------|
| Foursquare | 0.02867 | 0.04446 | 0.06681 | 0.115 |
| Yelp | 0.031421 | 0.05193 | 0.085184 | 0.1479221 |
Details for MAP:
| Dataset | MAP@5 | MAP@10 | MAP@20 | MAP@50 |
| ---------- | ------------ | -------------| ---------------| ------------|
| Foursquare | 0.01733 | 0.01987 | 0.02219 | 0.02491 |
| Yelp | 0.0202166 | 0.021 | 0.0231568 | 0.026059 |
Details for NDCG:
| Dataset | NDCG@5 | NDCG@10 | NDCG@20 | NDCG@50 |
| ---------- | ------------ | -------------| ---------------| -------------|
| Foursquare | 0.04894 | 0.04192 | 0.03448 | 0.02585 |
| Yelp | 0.03161 | 0.0279923 | 0.02425 | 0.0186004 |
- The performance of our framework on Foursquare.
- The performance of our framework on Yelp.
- python==3.7
We use two real-world LBSN datasets from Foursquare and Yep.
Statistics:
| Dataset | Number of users | Number of POIs | Number of categories | Number of check-ins | Number of social links | User-POI matrix density|
| ---------- | --------------- | -------------- | ---------------------| ---------------------- |-------------------------|----------------------- |
| Foursquare | 2,551 | 13,474 | 10 | 124,933 | 32,512 |0.291% |
| Yelp | 30,887 | 30,887 | 624 | 860,888 | 860,888 |0.14% |
1.python recommendation_Foursquare.py
2.recommendation_Yelp.py
Please cite our paper if you use the code or datasets:
@inproceedings{su2020fgrec,
title={FGRec: A Fine-Grained Point-of-Interest Recommendation Framework by Capturing Intrinsic Influences},
author={Yijun Su, Jia-Dong Zhang, Xiang Li, Daren Zha, Ji Xiang, Wei Tang and Neng Gao},
booktitle={IEEE International Joint Conference on Neural Networks, {IJCNN} 2020},
pages={1-9},
doi={10.1109/IJCNN48605.2020.9207571},
year={2020}
}
If you have any questions, please contact us by suyijun.ucas@gmail.com, we will be happy to assist.
Last Update Date: October 1, 2021