Code-for-KP4SR-master
所属分类:自然语言处理
开发工具:Python
文件大小:0KB
下载次数:0
上传日期:2023-09-10 00:58:34
上 传 者:
sh-1993
说明: 翟建阳、郑夏武、王昌东、李慧和田永红。顺序推荐的知识提示调整,ACMMM2023。,
(Jianyang Zhai, Xiawu Zheng, Chang-Dong Wang, Hui Li and Yonghong Tian. Knowledge Prompt-tuning for Sequential Recommendation, ACMMM2023.,)
文件列表:
data/ (0, 2023-09-09)
data/books/ (0, 2023-09-09)
data/books/datamaps.json (4871021, 2023-09-09)
data/books/entity2text.json (4646768, 2023-09-09)
data/books/item2entity.json (719554, 2023-09-09)
data/books/relation2template.json (1103, 2023-09-09)
data/books/sequential_data.txt (4692667, 2023-09-09)
data/books/triple2dict.json (17316265, 2023-09-09)
data/books/user_id2name.pkl (1839027, 2023-09-09)
env_npu.sh (1726, 2023-09-09)
images/ (0, 2023-09-09)
images/ab418be92f2addcf5f72c6438e3d47c9388bb248495d3c572c7c9988bb2420b9.png (278729, 2023-09-09)
notebooks/ (0, 2023-09-09)
notebooks/evaluate/ (0, 2023-09-09)
notebooks/evaluate/bleu.py (3475, 2023-09-09)
notebooks/evaluate/metrics4rec.py (11521, 2023-09-09)
notebooks/evaluate/rouge.py (10502, 2023-09-09)
notebooks/evaluate/utils.py (9424, 2023-09-09)
notebooks/utils.py (1829, 2023-09-09)
scripts/ (0, 2023-09-09)
scripts/modelarts_test.sh (472, 2023-09-09)
scripts/modelarts_train.sh (510, 2023-09-09)
src/ (0, 2023-09-09)
src/dist_utils.py (8074, 2023-09-09)
src/main.py (13278, 2023-09-09)
src/mask_amazon_templates.py (4970, 2023-09-09)
src/mask_flm_1b_templates.py (4826, 2023-09-09)
src/mask_movielens_templates.py (4687, 2023-09-09)
src/modeling_p5.py (26541, 2023-09-09)
src/param.py (6046, 2023-09-09)
src/pretrain_data.py (20263, 2023-09-09)
src/pretrain_model.py (4117, 2023-09-09)
src/test_sequential.py (10090, 2023-09-09)
src/tokenization.py (7997, 2023-09-09)
src/trainer_base.py (6095, 2023-09-09)
src/utils.py (1829, 2023-09-09)
# KP4SR
The source code for our paper: *Knowledge Prompt-tuning for Sequential Recommendation*.
## Overview
![picture 2](https://github.com/AllminerLab/Code-for-KP4SR-master/blob/master/images/ab418be92f2addcf5f72c6438e3d47c9388bb248495d3c572c7c9988bb2420b9.png)
## Preparation
Our code runs on the Ascend 910 NPU of Huawei modelarts.
- Ascend 910ProA
- torch == 1.8.1+ascend.rc3.20221020
- torch-npu == 1.8.1rc3.post20221020
## Usage
- train: run scripts/modelarts_train.sh
- test: run scripts/modelarts_test.sh
Reference:
Jianyang Zhai, Xiawu Zheng, Chang-Dong Wang, Hui Li and Yonghong Tian. "Knowledge Prompt-tuning for Sequential Recommendation", ACMMM2023.
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