A Study on Advertisements in The Chinese Recorder and Missionary Journal

The Chinese Recorder and Missionary Journal is one of the most valued English literature in China’s history of Christianity and the key publications of missionaries from the second half of the 19th Century to the first half of the 20th Century.The advertisements in it have not been properly stressed by the academic world,most of which are even deleted in the bound volumes.This paper aims to give a preliminary study on the advertisements in Chinese Recorder and Missionary Journal,comparing and analyzing advertisers,slogans and text structures and appeal methods of advertisements of shipping,banking,schools and book introduction in Chinese Recorder and Missionary Journal,thus demonstrating its significance in China’s modern advertising industry and Sino-western commercial trade and cultural exchange.

Data Masking for Chinese Electronic Medical Records with Named Entity Recognition

With the rapid development of information technology,the electronifi-cation of medical records has gradually become a trend.In China,the population base is huge and the supporting medical institutions are numerous,so this reality drives the conversion of paper medical records to electronic medical records.Electronic medical records are the basis for establishing a smart hospital and an important guarantee for achieving medical intelligence,and the massive amount of electronic medical record data is also an important data set for conducting research in the medical field.However,electronic medical records contain a large amount of private patient information,which must be desensitized before they are used as open resources.Therefore,to solve the above problems,data masking for Chinese electronic medical records with named entity recognition is proposed in this paper.Firstly,the text is vectorized to satisfy the required format of the model input.Secondly,since the input sentences may have a long or short length and the relationship between sentences in context is not negligible.To this end,a neural network model for named entity recognition based on bidirectional long short-term memory(BiLSTM)with conditional random fields(CRF)is constructed.Finally,the data masking operation is performed based on the named entity recog-nition results,mainly using regular expression filtering encryption and principal component analysis(PCA)word vector compression and replacement.In addi-tion,comparison experiments with the hidden markov model(HMM)model,LSTM-CRF model,and BiLSTM model are conducted in this paper.The experi-mental results show that the method used in this paper achieves 92.72%Accuracy,92.30%Recall,and 92.51%F1_score,which has higher accuracy compared with other models.

Systematic Recording of Chinese Storytelling Art

Chinese Storytelling; Gem of theWorld Oral HeritageAccording to historical records, storytelling,or "Shuoshu", had already become a professionsince the Song Dynasty (960-1279). In theprocess of the increasing urbanization ever since,the storyteller was regarded as an integral

Overview of CCKS 2020 Task 3: Named Entity Recognition and Event Extraction in Chinese Electronic Medical Records

The China Conference on Knowledge Graph and Semantic Computing(CCKS)2020 Evaluation Task 3 presented clinical named entity recognition and event extraction for the Chinese electronic medical records.Two annotated data sets and some other additional resources for these two subtasks were provided for participators.This evaluation competition attracted 354 teams and 46 of them successfully submitted the valid results.The pre-trained language models are widely applied in this evaluation task.Data argumentation and external resources are also helpful.

Word Embedding Bootstrapped Deep Active Learning Method to Information Extraction on Chinese Electronic Medical Record

Electronic medical record (EMR) containing rich biomedical information has a great potential in disease diagnosis and biomedical research. However, the EMR information is usually in the form of unstructured text, which increases the use cost and hinders its applications. In this work, an effective named entity recognition (NER) method is presented for information extraction on Chinese EMR, which is achieved by word embedding bootstrapped deep active learning to promote the acquisition of medical information from Chinese EMR and to release its value. In this work, deep active learning of bi-directional long short-term memory followed by conditional random field (Bi-LSTM+CRF) is used to capture the characteristics of different information from labeled corpus, and the word embedding models of contiguous bag of words and skip-gram are combined in the above model to respectively capture the text feature of Chinese EMR from unlabeled corpus. To evaluate the performance of above method, the tasks of NER on Chinese EMR with “medical history” content were used. Experimental results show that the word embedding bootstrapped deep active learning method using unlabeled medical corpus can achieve a better performance compared with other models.

A Book Series Recording Cultural Exchange between China and the West

“Chinese Studies in the West:The Chinese Record”is a book series consisting of works written by Westerners who went to China from the 18th to the early 20th century,each of which contains a Chinese introduction and translations of the book's core information followed by the reprint of the original text for scholars to study and research.From 2009 to 2021,13 volumes have been published,with a total of 130 titles.This article will discuss the different types of Westerners in the Series,the activities they engaged in while they were in China or related to China,the books they wrote and their opinions towards China and its people.It will also explore the Series'social impact and its value to the study of Sino-Western culture exchanges.