Mining Hot Research Topics based on Complex Network Analysis - A Case Study on Regenerative Medicine

Rong-Qiang Zeng, Hong-Shen Pang, Xiao-Chu Qin, Yi-Bing Song, Yi Wen, Zheng-Yin Hu, Ning Yang, Hong-Mei Guo, Qian Li

2017

Abstract

In order to mine the hot research topics of a certain field, we propose a hypervolume-based selection algorithm based on the complex network analysis, which employs a hypervolume indicator to select the hot research topics from the network in the considered field. We carry out the experiments in the field of regenerative medicine, and the experimental results indicate that our proposed method can effectively find the hot research topics in this field. The performance analysis sheds lights on the ways to further improvements.

Paper Citation

in Harvard Style

Zeng R., Pang H., Qin X., Song Y., Wen Y., Hu Z., Yang N., Guo H. and Li Q. (2017). Mining Hot Research Topics based on Complex Network Analysis - A Case Study on Regenerative Medicine.In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, ISBN 978-989-758-271-4, pages 263-268. DOI: 10.5220/0006504802630268

in Bibtex Style

@conference{kdir17,
author={Rong-Qiang Zeng and Hong-Shen Pang and Xiao-Chu Qin and Yi-Bing Song and Yi Wen and Zheng-Yin Hu and Ning Yang and Hong-Mei Guo and Qian Li},
title={Mining Hot Research Topics based on Complex Network Analysis - A Case Study on Regenerative Medicine},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,},
year={2017},
pages={263-268},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006504802630268},
isbn={978-989-758-271-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,
TI - Mining Hot Research Topics based on Complex Network Analysis - A Case Study on Regenerative Medicine
SN - 978-989-758-271-4
AU - Zeng R.
AU - Pang H.
AU - Qin X.
AU - Song Y.
AU - Wen Y.
AU - Hu Z.
AU - Yang N.
AU - Guo H.
AU - Li Q.
PY - 2017
SP - 263
EP - 268
DO - 10.5220/0006504802630268