DISA: A Scientific Writing Advisor with Deep Information Structure Analysis
Abstract
This paper demonstrates DISA, a higher-level writing assistant system, which analyzes the information structure of abstracts, and retrieves the knowledge according to the research goals from the related work. By incorporating the latest neural-network technologies including linguistically-informed neural-network and autoencoder, we construct an intelligent system which extends the scope of computer-aided writing.
Cite
Text
Huang and Chen. "DISA: A Scientific Writing Advisor with Deep Information Structure Analysis." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/773Markdown
[Huang and Chen. "DISA: A Scientific Writing Advisor with Deep Information Structure Analysis." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/huang2017ijcai-disa/) doi:10.24963/IJCAI.2017/773BibTeX
@inproceedings{huang2017ijcai-disa,
title = {{DISA: A Scientific Writing Advisor with Deep Information Structure Analysis}},
author = {Huang, Hen-Hsen and Chen, Hsin-Hsi},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2017},
pages = {5229-5231},
doi = {10.24963/IJCAI.2017/773},
url = {https://mlanthology.org/ijcai/2017/huang2017ijcai-disa/}
}