Title
A Novel Algorithm of Expansion Term Selection and Weight Assignment for Query Expansion of Chinese EMR Retrieval.
Abstract
The techniques of information retrieval eliminate the difficulty of finding specific information in electronic medical records (EMR), and the methods of query expansion (QE) improve the recall of EMR retrieval. However, most existing QE methods of EMR retrieval can’t get high-quality expansion terms and corresponding weights for Chinese EMR retrieval because of low-quality sources and improper calculation methods. In this paper, we propose a novel algorithm of expansion term selection and weight assignment for QE of Chinese EMR retrieval based on the clinical needs and unique characteristics of Chinese medical terms. The algorithm first selects expansion terms from a high quality Chinese medical knowledge graph and standard medical term sets, which can ensure the quality of expansion terms. Then it assigns weights to the selected expansion terms based on semantic similarities and manually designed expansion categories that reflect the opinions of medical experts. Experiment results show that our algorithm gets higher-quality expansion terms and more rational weights compared with four benchmark algorithms, using Precision at 10, Recall, Mean Average Precision and Binary Preference-based Measure as evaluation metrics, which implies that our algorithm can significantly improve the effectiveness of QE.
Year
DOI
Venue
2020
10.1109/BIBM49941.2020.9313210
BIBM
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Songchun Yang100.34
Xiangwen Zheng200.34
Fan Tong302.03
Huajian Mao402.70
Zhao Dongsheng506.42