| Mining Hot Research Topics based on Complex Network Analysis - A Case Study on Regenerative Medicine | |
Ceng RQ(曾荣强)1,3; Pang HS(庞弘燊)5 ; Tan XC(覃筱楚)2; Song YB(宋亦兵)2; Wen Y(文奕)1; Hu ZY(胡正银)1; Yang N(杨宁)1; Guo HM(郭红梅)4; Qian L(钱力)4; Hu ZY(胡正银)
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| 2017-11 | |
| Conference Name | the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management |
| Conference Date | 2017.11.1-2017.11.3 |
| Conference Place | 葡萄牙丰沙尔 |
| 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. |
| Keyword | Hot Research Topics Modularity Function Regenerative Medicine Community Detection Hypervolume Indicator |
| DOI | 10.5220/0006504802630268 |
| Language | 英语 |
| Citation statistics | |
| Document Type | 会议论文 |
| Identifier | http://ir.las.ac.cn/handle/12502/9600 |
| Collection | 中国科学院成都文献情报中心_信息技术部 |
| Corresponding Author | Hu ZY(胡正银) |
| Affiliation | 1.中国科学院成都文献情报中心 2.中国科学院广州生物医药与健康研究院 3.西南交通大学 4.中国科学院文献情报中心 5.深圳大学 |
| First Author Affilication | 中国科学院文献情报中心 |
| Recommended Citation GB/T 7714 | Ceng RQ,Pang HS,Tan XC,et al. Mining Hot Research Topics based on Complex Network Analysis - A Case Study on Regenerative Medicine[C],2017. |
| Files in This Item: | Download All | |||||
| File Name/Size | DocType | Version | Access | License | ||
| KDIR_2017_29.pdf（597KB） | 会议论文 | 开放获取 | CC BY-NC-SA | View Download | ||
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