Knowledge Commons of Institute of Automation，CAS
| ParagraphVector Based Retrieval Model for Similar Cases Recommendation | |
Zhao, Yifei1 ; Wang, Jing1; Wang, Feiyue1; Shi, Xiaobo2
| |
| 2016 | |
| 会议名称 | the 12th World Congress on Intelligent Control and Automation |
| 会议录名称 | Proceedings of the 12th World Congress on Intelligent Control and Automation |
| 会议日期 | 2016 |
| 会议地点 | Guilin |
| 摘要 | none;
Internet inquiry is playing an increasingly
important role as the complement of the traditional medical
service system, especially the similar cases recommendation. It
can not only save the patients’ waiting time, but also make use of
the historical resources, for many cases with the same purpose
have been solved perfectly. However, because of the diversity and
non-standard of the patients’ descriptions, the inquiry platform
cannot find the cases with similar semantic easily. Most
traditional retrieval methods require the overlap of two sentences,
and this is not suitable with the diversity and non-standard
descriptions. In this paper, we try to utilize the sentences’
semantic representation in a continuous space to understand the
cases, and then recommend the similar cases. We also
incorporate it into query likelihood language models, trying to
get better results. Our experimental data are all collected from a
real internet inquiry platform, and the results show that our
methods significantly outperform the state-of-the-art translation
based methods for similar cases recommendation. |
| 关键词 | Internet Inquiry Similar Cases Recommendation Distributed Representation Data Mining |
| 收录类别 | EI |
| 文献类型 | 会议论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/11709 |
| 专题 | 多模态人工智能系统全国重点实验室_平行智能技术与系统团队 |
| 通讯作者 | Zhao, Yifei |
| 作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.Qingdao Academy of Intelligent Industries |
| 第一作者单位 | 中国科学院自动化研究所 |
| 通讯作者单位 | 中国科学院自动化研究所 |
| 推荐引用方式 GB/T 7714 | Zhao, Yifei,Wang, Jing,Wang, Feiyue,et al. ParagraphVector Based Retrieval Model for Similar Cases Recommendation[C],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 | ||
| Paragraph Vector Bas（264KB） | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 | ||
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