Skip to content

Commit 36011ac

Browse files
wangzhen38wangzhen38
authored
Merge branch 'master' into bug_fix_39
2 parents 5f8f41e + 23639e0 commit 36011ac

Some content is hidden

Large Commits have some content hidden by default. Use the searchbox below for content that may be hidden.

41 files changed

+3836
-17
lines changed

‎.gitattributes‎

Lines changed: 7 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,7 @@
1+
*.txt linguist-language=markdown
2+
*.png linguist-language=markdown
3+
*.md linguist-language=markdown
4+
*.1 linguist-language=markdown
5+
*.7 linguist-language=markdown
6+
7+

‎README_CN.md‎

Lines changed: 4 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -130,6 +130,7 @@ python -u tools/static_trainer.py -m models/rank/dnn/config.yaml # 静态图训
130130
| 召回 | [NCF](models/recall/ncf/)([文档](https://paddlerec.readthedocs.io/en/latest/models/recall/ncf.html)) | [Python CPU/GPU](https://aistudio.baidu.com/aistudio/projectdetail/3240152) | ✓ | ✓ | >=2.1.0 | [WWW 2017][Neural Collaborative Filtering](https://arxiv.org/pdf/1708.05031.pdf) |
131131
| 召回 | [TiSAS](models/recall/tisas/) | - | ✓ | ✓ | >=2.1.0 | [WSDM 2020][Time Interval Aware Self-Attention for Sequential Recommendation](https://cseweb.ucsd.edu/~jmcauley/pdfs/wsdm20b.pdf) |
132132
| 召回 | [ENSFM](models/recall/ensfm/) | - | ✓ | ✓ | >=2.1.0 | [IW3C2 2020][Eicient Non-Sampling Factorization Machines for Optimal Context-Aware Recommendation](http://www.thuir.cn/group/~mzhang/publications/TheWebConf2020-Chenchong.pdf) |
133+
| 召回 | [MHCN](models/recall/mhcn/) | - | ✓ | ✓ | >=2.1.0 | [WWW 2021][Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation](https://arxiv.org/pdf/2101.06448v3.pdf) |
133134
| 召回 | [GNN](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/recall/gnn/) | - | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [AAAI 2019][Session-based Recommendation with Graph Neural Networks](https://arxiv.org/abs/1811.00855) |
134135
| 召回 | [RALM](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/recall/look-alike_recall/) | - | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [KDD 2019][Real-time Attention Based Look-alike Model for Recommender System](https://arxiv.org/pdf/1906.05022.pdf) |
135136
| 排序 | [Logistic Regression](models/rank/logistic_regression/)([文档](https://paddlerec.readthedocs.io/en/latest/models/rank/logistic_regression.html)) | [Python CPU/GPU](https://aistudio.baidu.com/aistudio/projectdetail/3240481) | ✓ | x | >=2.1.0 | / |
@@ -159,9 +160,10 @@ python -u tools/static_trainer.py -m models/rank/dnn/config.yaml # 静态图训
159160
| 排序 | [Wide&Deep](models/rank/wide_deep/)([文档](https://paddlerec.readthedocs.io/en/latest/models/rank/wide_deep.html)) | [Python CPU/GPU](https://aistudio.baidu.com/aistudio/projectdetail/3238421) | ✓ | x | >=2.1.0 | [DLRS 2016][Wide & Deep Learning for Recommender Systems](https://dl.acm.org/doi/pdf/10.1145/2988450.2988454) |
160161
| 排序 | [FGCNN](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/fgcnn/) | - | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [WWW 2019][Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction](https://arxiv.org/pdf/1904.04447.pdf) |
161162
| 排序 | [Fibinet](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/fibinet/) | - | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [RecSys19][FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction]( https://arxiv.org/pdf/1905.09433.pdf) |
162-
| 排序 | [Flen](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/flen/) | - | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [2019][FLEN: Leveraging Field for Scalable CTR Prediction]( https://arxiv.org/pdf/1911.04690.pdf) |
163+
| 排序 | [FLEN](models/rank/flen/) | - | ✓ | ✓ | >=2.1.0 | [2019][FLEN: Leveraging Field for Scalable CTR Prediction]( https://arxiv.org/pdf/1911.04690.pdf) |
163164
| 排序 | [DeepRec](models/rank/deeprec/) | - | ✓ | ✓ | >=2.1.0 | [2017][Training Deep AutoEncoders for Collaborative Filtering](https://arxiv.org/pdf/1708.01715v3.pdf) |
164-
| 排序 | [AutoFIS](models/rank/autofis/) | - | ✓ | ✓ | >=2.1.0 | [KDD 2020][AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction](https://arxiv.org/pdf/2003.11235v3.pdf) | | - | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [2019][FLEN: Leveraging Field for Scalable CTR Prediction]( https://arxiv.org/pdf/1911.04690.pdf) |
165+
| 排序 | [AutoFIS](models/rank/autofis/) | - | ✓ | ✓ | >=2.1.0 | [KDD 2020][AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction](https://arxiv.org/pdf/2003.11235v3.pdf)
166+
| 排序 | [DCN_V2](models/rank/dcn_v2/) | - | ✓ | ✓ | >=2.1.0 | [WWW 2021][DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems](https://arxiv.org/pdf/2008.13535v2.pdf)
165167
| 多任务 | [PLE](models/multitask/ple/)([文档](https://paddlerec.readthedocs.io/en/latest/models/multitask/ple.html)) | [Python CPU/GPU](https://aistudio.baidu.com/aistudio/projectdetail/3238938) | ✓ | ✓ | >=2.1.0 | [RecSys 2020][Progressive Layered Extraction (PLE): A Novel Multi-Task Learning (MTL) Model for Personalized Recommendations](https://dl.acm.org/doi/abs/10.1145/3383313.3412236) |
166168
| 多任务 | [ESMM](models/multitask/esmm/)([文档](https://paddlerec.readthedocs.io/en/latest/models/multitask/esmm.html)) | [Python CPU/GPU](https://aistudio.baidu.com/aistudio/projectdetail/3238583) | ✓ | ✓ | >=2.1.0 | [SIGIR 2018][Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate](https://arxiv.org/abs/1804.07931) |
167169
| 多任务 | [MMOE](models/multitask/mmoe/)([文档](https://paddlerec.readthedocs.io/en/latest/models/multitask/mmoe.html)) | [Python CPU/GPU](https://aistudio.baidu.com/aistudio/projectdetail/3238934) | ✓ | ✓ | >=2.1.0 | [KDD 2018][Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts](https://dl.acm.org/doi/abs/10.1145/3219819.3220007) |

‎README_EN.md‎

Lines changed: 3 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -120,6 +120,7 @@ python -u tools/static_trainer.py -m models/rank/dnn/config.yaml # Training wit
120120
| Recall | [NCF](models/recall/ncf/)<br>([doc](https://paddlerec.readthedocs.io/en/latest/models/recall/ncf.html)) | [Python CPU/GPU](https://aistudio.baidu.com/aistudio/projectdetail/3240152) | ✓ | ✓ | >=2.1.0 | [WWW 2017][Neural Collaborative Filtering](https://arxiv.org/pdf/1708.05031.pdf) |
121121
| Recall | [TiSAS](models/recall/tisas/) | - | ✓ | ✓ | >=2.1.0 | [WSDM 2020][Time Interval Aware Self-Attention for Sequential Recommendation](https://cseweb.ucsd.edu/~jmcauley/pdfs/wsdm20b.pdf) |
122122
| Recall | [ENSFM](models/recall/ensfm/) | - | ✓ | ✓ | >=2.1.0 | [IW3C2 2020][Eicient Non-Sampling Factorization Machines for Optimal Context-Aware Recommendation](http://www.thuir.cn/group/~mzhang/publications/TheWebConf2020-Chenchong.pdf) |
123+
| Recall | [MHCN](models/recall/mhcn/) | - | ✓ | ✓ | >=2.1.0 | [WWW 2021][Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation](https://arxiv.org/pdf/2101.06448v3.pdf) |
123124
| Recall | [GNN](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/recall/gnn/) | - | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [AAAI 2019][Session-based Recommendation with Graph Neural Networks](https://arxiv.org/abs/1811.00855) |
124125
| Recall | [RALM](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/recall/look-alike_recall/) | - | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [KDD 2019][Real-time Attention Based Look-alike Model for Recommender System](https://arxiv.org/pdf/1906.05022.pdf) |
125126
| Rank | [Logistic Regression](models/rank/logistic_regression/)<br>([doc](https://paddlerec.readthedocs.io/en/latest/models/rank/logistic_regression.html)) | [Python CPU/GPU](https://aistudio.baidu.com/aistudio/projectdetail/3240481) | ✓ | x | >=2.1.0 | / |
@@ -149,9 +150,10 @@ python -u tools/static_trainer.py -m models/rank/dnn/config.yaml # Training wit
149150
| Rank | [Wide&Deep](models/rank/wide_deep/)<br>([doc](https://paddlerec.readthedocs.io/en/latest/models/rank/wide_deep.html)) | [Python CPU/GPU](https://aistudio.baidu.com/aistudio/projectdetail/3238421) | ✓ | x | >=2.1.0 | [DLRS 2016][Wide & Deep Learning for Recommender Systems](https://dl.acm.org/doi/pdf/10.1145/2988450.2988454) |
150151
| Rank | [FGCNN](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/fgcnn/) | - | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [WWW 2019][Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction](https://arxiv.org/pdf/1904.04447.pdf) |
151152
| Rank | [Fibinet](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/fibinet/) | - | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [RecSys19][FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction]( https://arxiv.org/pdf/1905.09433.pdf) |
152-
| Rank | [Flen](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/flen/) | - | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [2019][FLEN: Leveraging Field for Scalable CTR Prediction]( https://arxiv.org/pdf/1911.04690.pdf) |
153+
| Rank | [FLEN](models/rank/flen/) | - | ✓ | ✓ | >=2.1.0 | [2019][FLEN: Leveraging Field for Scalable CTR Prediction]( https://arxiv.org/pdf/1911.04690.pdf) |
153154
| Rank | [DeepRec](models/rank/deeprec/) | - | ✓ | ✓ | >=2.1.0 | [2017][Training Deep AutoEncoders for Collaborative Filtering](https://arxiv.org/pdf/1708.01715v3.pdf) |
154155
| Rank | [AutoFIS](models/rank/autofis/) | - | ✓ | ✓ | >=2.1.0 | [KDD 2020][AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction](https://arxiv.org/pdf/2003.11235v3.pdf) |
156+
| Rank | [DCN_V2](models/rank/dcn_v2/) | - | ✓ | ✓ | >=2.1.0 | [WWW 2021][DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems](https://arxiv.org/pdf/2008.13535v2.pdf)
155157
| Multi-Task | [PLE](models/multitask/ple/)<br>([doc](https://paddlerec.readthedocs.io/en/latest/models/multitask/ple.html)) | [Python CPU/GPU](https://aistudio.baidu.com/aistudio/projectdetail/3238938) | ✓ | ✓ | >=2.1.0 | [RecSys 2020][Progressive Layered Extraction (PLE): A Novel Multi-Task Learning (MTL) Model for Personalized Recommendations](https://dl.acm.org/doi/abs/10.1145/3383313.3412236) |
156158
| Multi-Task | [ESMM](models/multitask/esmm/)<br>([doc](https://paddlerec.readthedocs.io/en/latest/models/multitask/esmm.html)) | [Python CPU/GPU](https://aistudio.baidu.com/aistudio/projectdetail/3238583) | ✓ | ✓ | >=2.1.0 | [SIGIR 2018][Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate](https://arxiv.org/abs/1804.07931) |
157159
| Multi-Task | [MMOE](models/multitask/mmoe/)<br>([doc](https://paddlerec.readthedocs.io/en/latest/models/multitask/mmoe.html)) | [Python CPU/GPU](https://aistudio.baidu.com/aistudio/projectdetail/3238934) | ✓ | ✓ | >=2.1.0 | [KDD 2018][Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts](https://dl.acm.org/doi/abs/10.1145/3219819.3220007) |

‎contributor.md‎

Lines changed: 5 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -12,10 +12,13 @@
1212
| [BERT4REC](models/rank/bert4rec/) | [jinweiluo](https://github.com/jinweiluo) | https://github.com/PaddlePaddle/PaddleRec/pull/624 | 论文复现赛第四期 |
1313
| [FAT_DeepFFM](models/rank/fat_deepffm/) | [LinJayan](https://github.com/LinJayan) | https://github.com/PaddlePaddle/PaddleRec/pull/651 | 论文复现赛第四期 |
1414
| [DeepRec](models/rank/deeprec/) | [chenjiyan2001](https://github.com/chenjiyan2001) | https://github.com/PaddlePaddle/PaddleRec/pull/647 | 论文复现赛第五期 |
15-
| [ENSFM](models/recal/ensfm/) | [renmada](https://github.com/renmada) | https://github.com/PaddlePaddle/PaddleRec/pull/618 | 论文复现赛第五期 |
16-
| [TiSAS](models/recal/tisas/) | [renmada](https://github.com/renmada) | https://github.com/PaddlePaddle/PaddleRec/pull/625 | 论文复现赛第五期 |
15+
| [ENSFM](models/recall/ensfm/) | [renmada](https://github.com/renmada) | https://github.com/PaddlePaddle/PaddleRec/pull/618 | 论文复现赛第五期 |
16+
| [TiSAS](models/recall/tisas/) | [renmada](https://github.com/renmada) | https://github.com/PaddlePaddle/PaddleRec/pull/625 | 论文复现赛第五期 |
1717
| [AutoFIS](models/rank/autofis/) | [renmada](https://github.com/renmada) | https://github.com/PaddlePaddle/PaddleRec/pull/660 | 论文复现赛第五期 |
1818
| [Dselect_K](models/multitask/dselect_k/) | [Andy1314Chen](https://github.com/Andy1314Chen) | https://github.com/PaddlePaddle/PaddleRec/pull/671 | 论文复现赛第五期 |
1919
| [MIND](models/recall/mind/) | [duyiqi17 ](https://github.com/duyiqi17) | https://github.com/PaddlePaddle/PaddleRec/pull/398 | 其他 |
20+
| [FLEN](models/rank/flen/) | [LinJayan](https://github.com/LinJayan) | https://github.com/PaddlePaddle/PaddleRec/pull/685 | 论文复现赛第五期 |
21+
| [MHCN](models/recall/mhcn/) | [Andy1314Chen](https://github.com/Andy1314Chen) | https://github.com/PaddlePaddle/PaddleRec/pull/679 | 论文复现赛第五期 |
22+
| [DCN_V2](models/rank/dcn_v2/) | [LinJayan](https://github.com/LinJayan) | https://github.com/PaddlePaddle/PaddleRec/pull/677 | 论文复现赛第五期 |
2023

2124
</div>

0 commit comments

Comments
 (0)