基于Adarank的中文电子病案检索排序技术研究

Zhang Ping, Wu Jinfa
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引用次数: 1

摘要

电子病历(EMR)贯穿于整个医疗活动的各个环节。如何快速准确地找到所需的电子病历已成为电子病历检索过程中的一个难点。介绍了一种利用排序学习AdaRank检索算法优化中文电子病历搜索引擎系统搜索结果排序的方法。对248份人工标注的中文电子病案,采用5种分类学习方法进行培训和测试。我们的AdaRank排序算法实现了NDCG@10的0.28178,ERR@10的0.38038,MAP@10的0.59368。与排序学习模型RankNet、LambdaRank、ListNet和LambdaMART相比,AdaRank方法具有更好的排序效果。
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Research on Search Ranking Technology of Chinese Electronic Medical Record Based on Adarank
Electronic Medical Records (EMR) run through every link in the whole medical activities. How to find the required EMR quickly and accurately has become a difficult point in the process of EMR retrieval. This paper introduces a method to optimize the sorting of search results in Chinese electronic medical record search engine system by using the sorting learning AdaRank retrieval algorithm. In 248 Chinese electronic medical records manually annotated, five sorting learning methods were used for training and testing. Our AdaRank sorting algorithm achieved NDCG@10 of 0.28178, ERR@10 of 0.38038 and MAP@10 of 0.59368. Compared with RankNet, the sorting learning model, LambdaRank, ListNet and LambdaMART, AdaRank methods have better sorting effect.
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