diff --git a/doc/imgs/dcn.JPG b/doc/imgs/dcn.JPG new file mode 100644 index 0000000000000000000000000000000000000000..8b41ced89aa0312049a42610e42f869f480c31bf Binary files /dev/null and b/doc/imgs/dcn.JPG differ diff --git a/doc/imgs/deepfm.JPG b/doc/imgs/deepfm.JPG new file mode 100644 index 0000000000000000000000000000000000000000..564d45dbe25b1fec9a1db60b749e5b1daff572f5 Binary files /dev/null and b/doc/imgs/deepfm.JPG differ diff --git a/doc/imgs/din.JPG b/doc/imgs/din.JPG new file mode 100644 index 0000000000000000000000000000000000000000..5195223cbf7e737e85a258ade9962d200cf80e35 Binary files /dev/null and b/doc/imgs/din.JPG differ diff --git a/doc/imgs/wide&deep.JPG b/doc/imgs/wide&deep.JPG new file mode 100644 index 0000000000000000000000000000000000000000..bc2177c73bd16274bfe3d87d0ed0bb6c3c48d1e8 Binary files /dev/null and b/doc/imgs/wide&deep.JPG differ diff --git a/doc/imgs/xdeepfm.JPG b/doc/imgs/xdeepfm.JPG new file mode 100644 index 0000000000000000000000000000000000000000..ad55040867f2a8370f63daca6dd5f7ec191a4e4f Binary files /dev/null and b/doc/imgs/xdeepfm.JPG differ diff --git a/models/contentunderstanding/readme.md b/models/contentunderstanding/readme.md index cbbc99d51826ed13dac35cd27df36cb5f89969bd..792518389cdfcc860ba31b14c1755a9964ea32bf 100644 --- a/models/contentunderstanding/readme.md +++ b/models/contentunderstanding/readme.md @@ -25,12 +25,12 @@ | TagSpace | 标签推荐 | [TagSpace: Semantic Embeddings from Hashtags (2014)](https://research.fb.com/publications/tagspace-semantic-embeddings-from-hashtags/) | | Classification | 文本分类 | [Convolutional neural networks for sentence classication (2014)](https://www.aclweb.org/anthology/D14-1181.pdf) | -TagSpace模型 +[TagSpace模型](https://research.fb.com/publications/tagspace-semantic-embeddings-from-hashtags)

-文本分类CNN模型 +[文本分类CNN模型](https://www.aclweb.org/anthology/D14-1181.pdf)

diff --git a/models/rank/readme.md b/models/rank/readme.md index 0f890e995f6cbfc9520f0f6719fbf08252194cf4..66f7e4969c450e50bfce22e925d30cc9192e2cfa 100755 --- a/models/rank/readme.md +++ b/models/rank/readme.md @@ -1,13 +1,13 @@ # 排序模型库 ## 简介 -我们提供了常见的排序任务中使用的模型算法的PaddleRec实现, 单机训练&预测效果指标以及分布式训练&预测性能指标等。实现的排序模型包括 [多层神经网络](http://gitlab.baidu.com/tangwei12/paddlerec/tree/develop/models/rank/dnn)、[Deep Cross Network](http://gitlab.baidu.com/tangwei12/paddlerec/tree/develop/models/rank/dcn)、[DeepFM](http://gitlab.baidu.com/tangwei12/paddlerec/tree/develop/models/rank/deepfm)、 [xDeepFM](http://gitlab.baidu.com/tangwei12/paddlerec/tree/develop/models/rank/xdeepfm)、[Deep Interest Network](http://gitlab.baidu.com/tangwei12/paddlerec/tree/develop/models/rank/din)、[Wide&Deep](http://gitlab.baidu.com/tangwei12/paddlerec/tree/develop/models/rank/wide_deep)。 +我们提供了常见的排序任务中使用的模型算法的PaddleRec实现, 单机训练&预测效果指标以及分布式训练&预测性能指标等。实现的排序模型包括 [多层神经网络](dnn)、[Deep Cross Network](dcn)、[DeepFM](deepfm)、 [xDeepFM](xdeepfm)、[Deep Interest Network](din)、[Wide&Deep](wide_deep)。 模型算法库在持续添加中，欢迎关注。 ## 目录 * [整体介绍](#整体介绍) - * [排序模型列表](#排序模型列表) + * [模型列表](#模型列表) * [使用教程](#使用教程) * [数据处理](#数据处理) * [训练](#训练) @@ -18,16 +18,41 @@ * [模型性能列表](#模型性能列表) ## 整体介绍 -### 排序模型列表 +### 模型列表 | 模型 | 简介 | 论文 | | :------------------: | :--------------------: | :---------: | | DNN | 多层神经网络 | -- | -| wide&deep | Deep + wide(LR) | [Wide & Deep Learning for Recommender Systems](https://dl.acm.org/doi/abs/10.1145/2988450.2988454)(2016) | -| DeepFM | DeepFM | [DeepFM: A Factorization-Machine based Neural Network for CTR Prediction](https://arxiv.org/abs/1703.04247)(2017) | -| xDeepFM | xDeepFM | [xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems](https://dl.acm.org/doi/abs/10.1145/3219819.3220023)(2018) | -| DCN | Deep Cross Network | [Deep & Cross Network for Ad Click Predictions](https://dl.acm.org/doi/abs/10.1145/3124749.3124754)(2017) | -| DIN | Deep Interest Network | [Deep Interest Network for Click-Through Rate Prediction](https://dl.acm.org/doi/abs/10.1145/3219819.3219823)(2018) | +| wide&deep | Deep + wide(LR) | [Wide & Deep Learning for Recommender Systems](https://dl.acm.org/doi/pdf/10.1145/2988450.2988454)(2016) | +| DeepFM | DeepFM | [DeepFM: A Factorization-Machine based Neural Network for CTR Prediction](https://arxiv.org/pdf/1703.04247.pdf)(2017) | +| DCN | Deep Cross Network | [Deep & Cross Network for Ad Click Predictions](https://dl.acm.org/doi/pdf/10.1145/3124749.3124754)(2017) | +| xDeepFM | xDeepFM | [xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems](https://dl.acm.org/doi/pdf/10.1145/3219819.3220023)(2018) | +| DIN | Deep Interest Network | [Deep Interest Network for Click-Through Rate Prediction](https://dl.acm.org/doi/pdf/10.1145/3219819.3219823)(2018) | + +[wide&deep](https://dl.acm.org/doi/pdf/10.1145/2988450.2988454): +

+ +

+ +[DeepFM](https://arxiv.org/pdf/1703.04247.pdf): +

+ +

+ +[XDeepFM](https://dl.acm.org/doi/pdf/10.1145/3219819.3220023): +

+ +

+ +[DCN](https://dl.acm.org/doi/pdf/10.1145/3124749.3124754): +

+ +

+ +[DIN](https://dl.acm.org/doi/pdf/10.1145/3219819.3219823): +

+ +

## 使用教程 ### 数据处理 @@ -66,4 +91,4 @@ | Criteo | DCN | -- | -- | -- | -- | -- | | Criteo | xDeepFM | -- | -- | -- | -- | -- | | Census-income Data | Wide&Deep | -- | -- | -- | -- | -- | -| Amazon Product | DIN | -- | -- | -- | -- | -- | \ No newline at end of file +| Amazon Product | DIN | -- | -- | -- | -- | -- |