Knowledge Commons of Institute of Automation,CAS
MH-ARM: a Multi-mode and High-value Association Rule Mining Technique for Healthcare Data Analysis | |
Yang, Libao; Li, Zhe; Luo, Guan | |
2016 | |
会议名称 | International Conference on Computational Science and Computational Intelligence |
会议日期 | 15-17 Dec. 2016 |
会议地点 | Las Vegas, NV, USA |
出版者 | IEEE |
摘要 | The association rules mining process enables the end users to analyze, understand, and use the extracted knowledge in an intelligent system or to support the decision-making processes. To find valuable association rules from a large number of redundant rules, this paper proposes a deeper mining process, multi-mode and high value association rules mining (MH-ARM). This method takes into account the category information, the size of the item set, natural semantics, various metrics, and effective visualization of results. The process can effectively reduce the number of rules and improve the value and accuracy of the rules screened out for auxiliary diagnosis. In the end, the experimental data of rhinitis were analyzed and the effectiveness of the process was verified. |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/40568 |
专题 | 多模态人工智能系统全国重点实验室_视频内容安全 |
通讯作者 | Luo, Guan |
作者单位 | NLPR, Institute of Automation, Chinese Academy of Sciences |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Yang, Libao,Li, Zhe,Luo, Guan. MH-ARM: a Multi-mode and High-value Association Rule Mining Technique for Healthcare Data Analysis[C]:IEEE,2016. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
2016Yang_MH-ARM_0788(492KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论