PI2I/PI2I

--- license: apache-2.0 tags: - recommender-system size_categories: - 1B<n<10B --- # Dataset Overview The dataset presented in our paper *"PI2I: A Personalized Item-Based Collaborative Filtering Retrieval Framework"*, which has been accepted by the **Industry Track of TheWebConf 2026**, comprises **130 million real-world user-item interactions** collected from Taobao. Below is a summary of key statistics (<time,userid,itemid>): | Description | Value | |---------------------------------------------|---------------| | Total number of interactions (rows) | 130,828,023 | | Number of distinct users (`userid`) | 705,647 | | &nbsp;&nbsp;&nbsp;&nbsp;*Note:* Slight discrepancies may exist compared to the values reported in the paper due to hash collisions. | | | Number of distinct items (`itemid`) | 20,351,625 | | &nbsp;&nbsp;&nbsp;&nbsp;*Note:* Slight discrepancies may exist compared to the values reported in the paper due to hash collisions. | | | Time span | 23 days | | Average user interaction count | 185 | | Maximum user interaction count | 20,894 | | Minimum user interaction count | 1 | | Sparsity | 99.9% | | &nbsp;&nbsp;&nbsp;&nbsp;*(calculated as $1 - \frac{130,828,023}{20,351,625 \times 705,647}$)* | | Please cite the following paper if you find our code helpful: @article{wang2026pi2i, title={PI2I: A Personalized Item-Based Collaborative Filtering Retrieval Framework}, author={Wang, Shaoqing and Ma, Yingcai and Fu, Kairui and Wang, Ziyang and Huang, Dunxian and Yan, Yuliang and Wu, Jian}, journal={arXiv preprint arXiv:2601.16815}, year={2026} }