[Pan, Min] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.
[Jiang, Xingpeng; He, Tingting; Zhang, Yue] Cent China Normal Univ, Sch Comp Sci, Wuhan 430079, Hubei, Peoples R China.
通讯机构：
[Zhang, Yue] C
Cent China Normal Univ, Sch Comp Sci, Wuhan 430079, Hubei, Peoples R China.
语种：
英文
关键词：
Computation theory;Decision support systems;Clinical decision support;Clinical retrieval;Co-occurrence relationships;Electronic health record;Normalization methods;Pseudo relevance feedback;Pseudo-relevance feedbacks;Term proximity;Intelligent computing
期刊：
Lecture Notes in Computer Science
ISSN：
0302-9743
年：
2018
卷：
10955
页码：
93-99
会议名称：
14th International Conference on Intelligent Computing, ICIC 2018
会议论文集名称：
Lecture Notes in Computer Science
会议时间：
15 August 2018 through 18 August 2018
会议地点：
Wuhan, PEOPLES R CHINA
会议主办单位：
[Pan, Min] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.^[Zhang, Yue;He, Tingting;Jiang, Xingpeng] Cent China Normal Univ, Sch Comp Sci, Wuhan 430079, Hubei, Peoples R China.
National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61532008]; National Key Research and Development Program of China [2017YFC0909502]
机构署名：
本校为第一且通讯机构
院系归属：
计算机学院
国家数字化学习工程技术研究中心
摘要：
In an actual electronic health record (EHR), patient notes are written with terse language and clinical jargons. However, most Pseudo Relevance Feedback (PRF) technique methods do not take into account the significant degree of candidate term in feedback documents and the co-occurrence relationship between a candidate term and a query term simultaneously. In this paper, we study how to incorporate proximity information into the Rocchio’s model, and propose a HAL-based Rocchio’s model, called HRoc. A new concept of term proximity feedback weig...
