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
专题复杂系统管理与控制国家重点实验室_先进控制与自动化
通讯作者Zhao, Yifei
作者单位1.Institute of Automation, Chinese Academy of Sciences
2.Qingdao Academy of Intelligent Industries
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.
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