Update README.md

Author: Weichen Shen

README.md

@@ -9,7 +9,7 @@
 
 
 [![Documentation Status](https://readthedocs.org/projects/deepctr-doc/badge/?version=latest)](https://deepctr-doc.readthedocs.io/)
-[![Build Status](https://travis-ci.com/shenweichen/DeepCTR.svg?branch=master)](https://travis-ci.com/shenweichen/DeepCTR)
+[![Build Status](https://travis-ci.org/shenweichen/DeepCTR.svg?branch=master)](https://travis-ci.org/shenweichen/DeepCTR)
 [![Coverage Status](https://coveralls.io/repos/github/shenweichen/DeepCTR/badge.svg?branch=master)](https://coveralls.io/github/shenweichen/DeepCTR?branch=master)
 [![Codacy Badge](https://api.codacy.com/project/badge/Grade/d4099734dc0e4bab91d332ead8c0bdd0)](https://www.codacy.com/app/wcshen1994/DeepCTR?utm_source=github.com&utm_medium=referral&utm_content=shenweichen/DeepCTR&utm_campaign=Badge_Grade)
 [![License](https://img.shields.io/github/license/shenweichen/deepctr.svg)](https://github.com/shenweichen/deepctr/blob/master/LICENSE)
@@ -31,4 +31,4 @@ Through  `pip install deepctr`  get the package and [**Get Started!**](https://d
 |Deep & Cross Network|[ADKDD 2017][Deep & Cross Network for Ad Click Predictions](https://arxiv.org/abs/1708.05123)|
 |Attentional Factorization Machine|[IJCAI 2017][Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks](http://www.ijcai.org/proceedings/2017/435)|
 |Neural Factorization Machine|[SIGIR 2017][Neural Factorization Machines for Sparse Predictive Analytics](https://arxiv.org/pdf/1708.05027.pdf)|
-|Deep Interest Network|[KDD 2018][Deep Interest Network for Click-Through Rate Prediction](https://arxiv.org/pdf/1706.06978.pdf)|
+|Deep Interest Network|[KDD 2018][Deep Interest Network for Click-Through Rate Prediction](https://arxiv.org/pdf/1706.06978.pdf)|