refine readme for rank and cu

models/contentunderstanding/readme.md

@@ -26,6 +26,7 @@
 | Classification | 文本分类 | [Convolutional neural networks for sentence classication (2014)](https://www.aclweb.org/anthology/D14-1181.pdf) |
 
 下面是每个模型的简介（注：图片引用自链接中的论文）
+
 [TagSpace模型](https://research.fb.com/publications/tagspace-semantic-embeddings-from-hashtags)
 <p align="center">
 <img align="center" src="../../doc/imgs/tagspace.png">

models/rank/readme.md

@@ -30,6 +30,7 @@
 | DIN | Deep Interest Network | [Deep Interest Network for Click-Through Rate Prediction](https://dl.acm.org/doi/pdf/10.1145/3219819.3219823)(2018) |
 
 下面是每个模型的简介（注：图片引用自链接中的论文）
+
 [wide&deep](https://dl.acm.org/doi/pdf/10.1145/2988450.2988454):
 <p align="center">
 <img align="center" src="../../doc/imgs/wide&deep.png">