Purpose: The thrust of this paper is to present a method for improving the accuracy of automatic indexing of Chinese-English mixed documents.Design/methodology/approach: Based on the inherent characteristics of Chines...Purpose: The thrust of this paper is to present a method for improving the accuracy of automatic indexing of Chinese-English mixed documents.Design/methodology/approach: Based on the inherent characteristics of Chinese-English mixed texts and the cybernetics theory,we proposed an integrated control method for indexing documents. It consists of 'feed-forward control','in-progress control' and 'feed-back control',aiming at improving the accuracy of automatic indexing of Chinese-English mixed documents. An experiment was conducted to investigate the effect of our proposed method.Findings: This method distinguishes Chinese and English documents in grammatical structures and word formation rules. Through the implementation of this method in the three phases of automatic indexing for the Chinese-English mixed documents,the results were encouraging. The precision increased from 88.54% to 97.10% and recall improved from97.37% to 99.47%.Research limitations: The indexing method is relatively complicated and the whole indexing process requires substantial human intervention. Due to pattern matching based on a bruteforce(BF) approach,the indexing efficiency has been reduced to some extent.Practical implications: The research is of both theoretical significance and practical value in improving the accuracy of automatic indexing of multilingual documents(not confined to Chinese-English mixed documents). The proposed method will benefit not only the indexing of life science documents but also the indexing of documents in other subject areas.Originality/value: So far,few studies have been published about the method for increasing the accuracy of multilingual automatic indexing. This study will provide insights into the automatic indexing of multilingual documents,especially Chinese-English mixed documents.展开更多
中文电子病历命名实体识别主要是研究电子病历病程记录文书数据集,文章提出对医疗手术麻醉文书数据集进行命名实体识别的研究。利用轻量级来自Transformer的双向编码器表示(A Lite Bidirectional Encoder Representation from Transform...中文电子病历命名实体识别主要是研究电子病历病程记录文书数据集,文章提出对医疗手术麻醉文书数据集进行命名实体识别的研究。利用轻量级来自Transformer的双向编码器表示(A Lite Bidirectional Encoder Representation from Transformers,ALBERT)预训练模型微调数据集和Tranfomers中的trainer训练器训练模型的方法,实现在医疗手术麻醉文书上识别手术麻醉事件命名实体与获取复杂麻醉医疗质量控制指标值。文章为医疗手术麻醉文书命名实体识别提供了可借鉴的思路,并且为计算复杂麻醉医疗质量控制指标值提供了一种新的解决方案。展开更多
基金supported by the Shanghai International Studies University(Grant No.:2011114061)
文摘Purpose: The thrust of this paper is to present a method for improving the accuracy of automatic indexing of Chinese-English mixed documents.Design/methodology/approach: Based on the inherent characteristics of Chinese-English mixed texts and the cybernetics theory,we proposed an integrated control method for indexing documents. It consists of 'feed-forward control','in-progress control' and 'feed-back control',aiming at improving the accuracy of automatic indexing of Chinese-English mixed documents. An experiment was conducted to investigate the effect of our proposed method.Findings: This method distinguishes Chinese and English documents in grammatical structures and word formation rules. Through the implementation of this method in the three phases of automatic indexing for the Chinese-English mixed documents,the results were encouraging. The precision increased from 88.54% to 97.10% and recall improved from97.37% to 99.47%.Research limitations: The indexing method is relatively complicated and the whole indexing process requires substantial human intervention. Due to pattern matching based on a bruteforce(BF) approach,the indexing efficiency has been reduced to some extent.Practical implications: The research is of both theoretical significance and practical value in improving the accuracy of automatic indexing of multilingual documents(not confined to Chinese-English mixed documents). The proposed method will benefit not only the indexing of life science documents but also the indexing of documents in other subject areas.Originality/value: So far,few studies have been published about the method for increasing the accuracy of multilingual automatic indexing. This study will provide insights into the automatic indexing of multilingual documents,especially Chinese-English mixed documents.
文摘中文电子病历命名实体识别主要是研究电子病历病程记录文书数据集,文章提出对医疗手术麻醉文书数据集进行命名实体识别的研究。利用轻量级来自Transformer的双向编码器表示(A Lite Bidirectional Encoder Representation from Transformers,ALBERT)预训练模型微调数据集和Tranfomers中的trainer训练器训练模型的方法,实现在医疗手术麻醉文书上识别手术麻醉事件命名实体与获取复杂麻醉医疗质量控制指标值。文章为医疗手术麻醉文书命名实体识别提供了可借鉴的思路,并且为计算复杂麻醉医疗质量控制指标值提供了一种新的解决方案。
