TY - GEN
T1 - CSSSketch2Code
T2 - 2nd International Conference on Advances in Artificial Intelligence, ICAAI 2018
AU - Han, Yi
AU - He, Jun
AU - Dong, Qiwen
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/10/6
Y1 - 2018/10/6
N2 - With the constantly increasing scale of the Internet and the users, the Internet applications have higher demands on the front-end web pages. Some web pages have single lattice structure and a relatively fixed HTML code template, which can be automatically generated. There have been research abroad using the deep learning on the task of automatically generating the web pages. However due to the basic encoder-decoder model adopted, the generalization ability of the model is not very robust. In this paper, we propose a novel method based on object detection and attention mechanism to automatically generate a web page with CSS style information. We use object detection to extend the original problem, which makes the model possible to detect the CSS style contents in the web page. Meanwhile we use attention mechanism to strengthen the model. Finally we propose our own dataset, based on which the experiment results show that method we proposed outperforms other existing methods.
AB - With the constantly increasing scale of the Internet and the users, the Internet applications have higher demands on the front-end web pages. Some web pages have single lattice structure and a relatively fixed HTML code template, which can be automatically generated. There have been research abroad using the deep learning on the task of automatically generating the web pages. However due to the basic encoder-decoder model adopted, the generalization ability of the model is not very robust. In this paper, we propose a novel method based on object detection and attention mechanism to automatically generate a web page with CSS style information. We use object detection to extend the original problem, which makes the model possible to detect the CSS style contents in the web page. Meanwhile we use attention mechanism to strengthen the model. Finally we propose our own dataset, based on which the experiment results show that method we proposed outperforms other existing methods.
KW - Attention mechanism
KW - Bidirectional long short term memory
KW - CSS
KW - Convolutional neural network
KW - Front-end pages automatic generation
KW - Object detection
UR - https://www.scopus.com/pages/publications/85061025638
U2 - 10.1145/3292448.3292455
DO - 10.1145/3292448.3292455
M3 - 会议稿件
AN - SCOPUS:85061025638
T3 - ACM International Conference Proceeding Series
SP - 29
EP - 35
BT - ICAAI 2018 - 2018 the 2nd International Conference on Advances in Artificial Intelligence
PB - Association for Computing Machinery
Y2 - 6 October 2018 through 8 October 2018
ER -