Mining Hot Research Topics based on Complex Network Analysis - A Case Study on Regenerative Medicine
文献类型：会议论文
| 作者 | 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
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| 出版日期 | 2017-11 |
| 会议名称 | the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management |
| 会议日期 | 2017.11.1-2017.11.3 |
| 会议地点 | 葡萄牙丰沙尔 |
| 关键词 | Hot Research Topics Modularity Function Regenerative Medicine Community Detection Hypervolume Indicator |
| 通讯作者 | 胡正银 |
| 英文摘要 | 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. |
| 语种 | 英语 |
| 源URL | [http://ir.las.ac.cn/handle/12502/9600]  |
| 专题 | 文献情报中心_中国科学院成都文献情报中心_信息技术部 |
| 作者单位 | 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 |
| 推荐引用方式 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]. 见:the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. 葡萄牙丰沙尔. 2017.11.1-2017.11.3. |
入库方式： OAI收割
来源：文献情报中心
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