Research and Analysis of Grammatical Error Correction Technology for Chinese Documents

With the widespread use of Chinese globally, the number of Chinese learners has been increasing, leading to various grammatical errors among beginners. Additionally, as domestic efforts to develop industrial information grow, electronic documents have also proliferated. When dealing with numerous electronic documents and texts written by Chinese beginners, manually written texts often contain hidden grammatical errors, posing a significant challenge to traditional manual proofreading. Correcting these grammatical errors is crucial to ensure fluency and readability. However, certain special types of text grammar or logical errors can have a huge impact, and manually proofreading a large number of texts individually is clearly impractical. Consequently, research on text error correction techniques has garnered significant attention in recent years. The advent and advancement of deep learning have paved the way for sequence-to-sequence learning methods to be extensively applied to the task of text error correction. This paper presents a comprehensive analysis of Chinese text grammar error correction technology, elaborates on its current research status, discusses existing problems, proposes preliminary solutions, and conducts experiments using judicial documents as an example. The aim is to provide a feasible research approach for Chinese text error correction technology.

Word Segmentation for Chinese Judicial Documents

Word segmentation is an integral step in many knowledge discovery applications. However, existing word segmentation methods have problems when applying to Chinese judicial documents:(1) existing methods rely on large-scale labeled data which is typically unavailable in judicial documents, and (2) judicial document has its own language features and writing formats. In this paper, a word segmentation method is proposed for Chinese judicial documents. The proposed method consists of two steps:(1) automatically generating some labeled data as legal dictionaries, and (2) applying a hybrid multilayer neural networks to do word segmentation incorporating legal dictionaries. Experiments are conducted on a dataset of Chinese judicial documents showing that the proposed model can achieve better results than the existing methods.

On the Combination of “The Textual Research on Historical Documents” and “The Comparative Study of Historical Data” —— and a Discussion on “The Law of Quan-ma and Gui-mei” in Chinese Language Studies

In Chinese language studies, both “The Textual Research on Historical Documents” and “The Comparative Study of Historical Data” are traditional in methodology and they both deserve being treasured, passed on, and further developed. It will certainly do harm to the development of academic research if any of the two methods is given unreasonable priority. The author claims that the best or one of the best methodologies of the historical study of Chinese language is the combination of the two, hence a new interpretation of “The Double-proof Method”. Meanwhile, this essay is also an attempt to put forward “The Law of Quan-ma and Gui-mei” in Chinese language studies, in which the author believes that it is not advisable to either treat Gui-mei as Quan-ma or vice versa in linguistic research. It is crucial for us to respect always the language facts first, which is considered the very soul of linguistics.

A method for improving the accuracy of automatic indexing of Chinese-English mixed documents

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.

Build Evidence Chain Relational Model Based on Chinese Judgment Document

The reasoning of judgment documents is the touchstone of justice. Attaching importance to the reasoning of judgment documents is essentially the embodiment of judiciary civilization. In order to promote the reform of judgment documents reasoning and improve the level of it, the technology of automated judgment documents reasoning evaluation has to be studied on. How to build evidence chain relational model is the basis and key to this technology.An approach is proposed to build evidence chain relational model based on Chinese judgment documents. Using automated text preprocessing for Chinese judgment documents creates semi-structured XML documents and extracts evidence set and fact set. The method of key elements extraction is used to obtain the keywords of evidence and facts. Calculating the degree of association can work out the connection points of evidence chain relational model. Tabular display and graphical display of evidence chain relational model can be realized.

Topic Model Based Text Similarity Measure for Chinese Judgment Document

In the recent informatization of Chinese courts, the huge amount of law cases and judgment documents, which were digital stored,has provided a good foundation for the research of judicial big data and machine learning. In this situation, some ideas about Chinese courts can reach automation or get better result through the research of machine learning, such as similar documents recommendation, workload evaluation based on similarity of judgement documents and prediction of possible relevant statutes. In trying to achieve all above mentioned, and also in face of the characteristics of Chinese judgement document, we propose a topic model based approach to measure the text similarity of Chinese judgement document, which is based on TF-IDF, Latent Dirichlet Allocation (LDA), Labeled Latent Dirichlet Allocation (LLDA) and other treatments. Combining with the characteristics of Chinese judgment document,we focus on the specific steps of approach, the preprocessing of corpus, the parameters choices of training and the evaluation of similarity measure result. Besides, implementing the approach for prediction of possible statutes and regarding the prediction accuracy as the evaluation metric, we designed experiments to demonstrate the reasonability of decisions in the process of design and the high performance of our approach on text similarity measure. The experiments also show the restriction of our approach which need to be focused in future work.

ENERGY CALCULUSIN CHINESE LANGUAGE SEGMENTATION

Based on cognitive science, the EnergyCalculus in Chinese language segmentation was presented to eliminate segmentation ambiguity. The notion of “EnergyCost” was advanced to denote the extent of the under standability of a certain segmentation. EnergyCost function was defined with Z notation. This approcah is effective to all natural language segmentation.

Chinese Sentiment Classification Using Extended Word2Vec

Sentiment analysis is now more and more important in modern natural language processing,and the sentiment classification is the one of the most popular applications.The crucial part of sentiment classification is feature extraction.In this paper,two methods for feature extraction,feature selection and feature embedding,are compared.Then Word2Vec is used as an embedding method.In this experiment,Chinese document is used as the corpus,and tree methods are used to get the features of a document:average word vectors,Doc2Vec and weighted average word vectors.After that,these samples are fed to three machine learning algorithms to do the classification,and support vector machine(SVM) has the best result.Finally,the parameters of random forest are analyzed.

Analysis of Adverse Reactions in the Treatment of COVID-19 with Three Chinese Patent Medicines and Three Herbal Formulas

Objective To explore the rules and characteristics of the adverse drug reactions(ADRs)of three Chinese patent medicines and three herbal formulas for the treatment of COVID-19,and to provide a reference for clinical safe medication.Methods The cases and ADR reports of the three Chinese patent medicines and three herbal formulas in PubMed,Web of Science,Springer Link,CNKI,Wanfang and VIP database were retrieved from December 2019 to May 2021.Then we extracted and analyzed the effective information included in the literature.Results and Conclusion According to the pre-developed retrieval plan,a total of 136 documents were obtained,and a total of 6 documents met the inclusion criteria finally.553 patients used three Chinese patent medicines and three herbal formulas,and there were 133 cases of adverse reactions.The adverse reactions of patients taking the three Chinese patent medicines and three herbal formulas can all be explained under the theory of traditional Chinese medicine,and the adverse reactions can be eliminated by adding or subtracting the flavor of the medicine or stopping the medicine.

Named entity recognition for Chinese construction documents based on conditional random field

Named entity recognition(NER)is essential in many natural language processing(NLP)tasks such as information extraction and document classification.A construction document usually contains critical named entities,and an effective NER method can provide a solid foundation for downstream applications to improve construction management efficiency.This study presents a NER method for Chinese construction documents based on conditional random field(CRF),including a corpus design pipeline and a CRF model.The corpus design pipeline identifies typical NER tasks in construction management,enables word-based tokenization,and controls the annotation consistency with a newly designed annotating specification.The CRF model engineers nine transformation features and seven classes of state features,covering the impacts of word position,part-of-speech(POS),and word/character states within the context.The F1-measure on a labeled construction data set is 87.9%.Furthermore,as more domain knowledge features are infused,the marginal performance improvement of including POS information will decrease,leading to a promising research direction of POS customization to improve NLP performance with limited data.

A new service model of document and information sharing among consortium members: The collaborative innovation practice of the NSLC and PASs

Purpose： This paper documents an exploration of an innovative approach to the sharing of documents and information among the members of the National Alliance of Academies of Sciences （NAAS） in China, based on the practice initiated by the National Science Library of the Chinese Academy of Sciences （NSLC）.Design/methodology/approach： Through interviews and user surveys, we analyzed the general information demands of users from provincial academies of sciences （PASs） and problems of their document and information service teams. Based on our findings, we designed targeted services to help Alliance members support their document resources, information services for science and technology （S＆T） decisions, and their knowledge transfer achievements. Furthermore, we offered training courses for provincial service teams, researchers, and administrators, to improve their information skills. These activities represent a new collaborative model for professional library consortia.Findings： To date, our service has been extended to all Alliance members, covering 19 provinces in China, and the NSLC service covers all aspects of knowledge services of Alliance members, from basic document delivery services to subject information analyses.Research limitations： Different PASs have different understandings of the role of the document and information services in the process of scientific research. These differences limit information service sharing of the NSLC with the PASs, and affect the service performance. For the sake of convenience, the original survey was conducted in only three provinces, which may not fully reflect the information needs of users in each Alliance institution. In addition, quantitative and qualitative analyses have been limited by the coverage of the sample.Practical implications： Document and information sharing has not only taken advantage of the NSLC knowledge service system and cooperation model, it has also enhanced the range of services of the NAAS in China.Originality/value： Based on knowledge service enhancements, the NAAS in China has formed a new kind of library consortium, which has broken the traditional library alliance model that was based mainly on the sharing of resources and services.

数字人文视域下馆藏清代土尔扈特档案文献可视化开发

清乾隆年间,土尔扈特部回归祖国事件形成的档案文献是中华民族共同体演进发展的档案佐证。数字人文环境下,对其档案进行可视化开发,可深入挖掘档案文本中的民族交往交流交融价值,提升档案馆知识服务效能,满足多元利用需求。据此,在阐释土尔扈特档案文献内涵外延、资源特征及其可视化开发理论与价值的基础上,提出以项目实施为依托的“多元共建共享”土尔扈特档案文献可视化开发方案。从档案的数据化整合、语义化处理与可视化服务等流程建构可视化开发路径,对于发掘土尔扈特档案文献中蕴含的爱国主义精神、维护新疆民族地区稳定发展,铸牢中华民族共同体意识具有重要现实意义。

交融互鉴:高昌国、唐西州各族民众社会生活研究——以吐鲁番出土文书为中心

吐鲁番位处丝路要冲,自古是民族往来汇聚之地,特别是高昌国、唐西州时期大量域外民族入籍此地,编户为民。利用吐鲁番出土文书从居住、生产、婚姻、信仰等方面考察各族民众的社会生活,可知当时各族民众房舍相望、田地相接,共享道路水渠,共同从事农业生产和手工业劳作,甚至族际通婚,宗教信仰转变等,在长期的杂居相处中交融互鉴。他们是丝绸之路上民族交流融合的典型缩影,是中华民族多元一体的重要组成部分,是增强中华民族共同体意识重要的文化认同资源和文化心理支撑。

《浙江畲族文书集成·文成卷》释文斠补

《浙江畲族文书集成·文成卷》整理了浙江省温州市文成县的900余件畲族文书,提供了宝贵的一手材料,具有重要的学术价值。然文书中异体俗字众多,导致释文存在误释、未释、缺释等问题,影响了文本的整理质量和科学利用。本文撷取七例文字方面的问题进行考校,求其确诂,以扫除语言文字障碍,恢复文书原貌,为学界提供精准的研究史料。

基于无人机和Rocfall的危岩落石特征分析与运动学模拟研究——以圆宝山隧道出口为例

丽香铁路位于云南省西北部,沿线山峦纵横,地形险峻,高山、峡谷、高原、盆地交错分布,地质构造复杂,新构造运动强烈,危岩落石发育。以丽江至香格里拉线的圆宝山隧道出口为研究对象,通过危岩现场地质调查、无人机航测获取影像数据,结合Rocfall软件模拟运动轨迹的技术方法,对潜在危岩体进行分析评价,较好地完成危岩体的地质灾害调查工作。结果表明:运用该方法可以精确查明危岩体的几何特征、空间位置及失稳模式,实现危岩的快速识别,以及得出危岩落石能量、弹跳高度、影响范围等信息,从而对潜在危岩体发育特征及危险性进行分析评价,针对性提出有效的防治措施。研究结论可以为危岩落石的灾害治理、防治设计提供一定的参考依据。

从学习方式演变审视语文知识观变革——基于语文课程文件的历时性分析

语文课程文件中描述学生学习行为的词语可以折射其蕴含的课程知识观念。改革开放以来,我国语文教学大纲和课程标准中的学习行为具有理解性记忆、实践性活动与个性化体悟等特点,并呈现从“以记中学为主”到“以做中学为主”的整体趋势。具体到内容领域,各类学习方式的组合变化反映了不同领域的语文知识观变革:识字与写字领域从强调数量到重视方法、经验与文化内涵;阅读领域从关注文本意义到强调文本建构;写作领域则从关注语篇建构到重视表达与交流的方法。

中医治疗老年骨质疏松性骨折方剂功效和证型分析

目的探讨治疗老年骨质疏松性骨折的方剂功效和中医证型,为临床辨证论治和遣方用药提供一些理论指导和参考依据。方法运用数据库对2021年5月31日以前的中药治疗老年骨质疏松性骨折的中文文献进行检索,整理、归纳和分析出相关方剂功效和中医证型。结果中药内服治疗老年骨质疏松性骨折前10位的中医证型依次为气滞血瘀、肝肾不足、骨断筋伤、脉络瘀阻、痹阻经络、气虚血瘀、气血亏虚、筋脉失养、邪毒内蕴、脾胃虚弱;前10位的方剂功效依次为活血化瘀、强筋壮骨、补益肝肾、接骨续筋、消肿止痛、行气止痛、舒筋活络、补气养血、健脾益气、益气活血。结论中药内服治疗老年骨质疏松性骨折的方剂功效可归纳为:活血化瘀、消肿止痛等为主的泻法;补益肝肾、强壮筋骨等为主的补法;益气活血的攻补兼施之法。中医证型可归纳为:气滞血瘀、骨断筋伤等为主的实证;肝肾不足、气血亏虚等为主的虚证;气虚血瘀为主的虚实夹杂之证。

基于数据挖掘探究中医古籍文献中水沟穴临床应用规律

目的:基于数据挖掘探究中医古籍文献中水沟穴的临床应用规律。方法:以《中华医典》收录的1156部古籍为检索范围,根据纳排标准筛选处方并建立数据库,运用Microsoft Excel 2019、RStudio 4.3.2软件对水沟穴的主治范围、腧穴配伍及施治方法等方面进行描述性分析与关联规则分析。结果:本研究最终纳入条文193条,涉及古籍93部。水沟穴主治病症以内科脑系和耳鼻喉科病症为主,单穴主治的优势病种共18种,分别为痫证、中恶、水肿、消渴、口僻、中风、厥证、唇风、乍喜乍哭、头痛、喘证、目不可视、癫狂、急惊风、卒死、鬼击、腰痛及黄疸;配伍主治的优势病种共17种,分别为中风、癫狂、腰痛、水肿、口僻、急惊风、厥证、鼻鼽、鼻衄、中恶、尸厥、鼻渊、慢惊风、卒死、口疮、口噤及鼻息肉。配伍腧穴共159个,包含十四经经穴及经外奇穴,高频腧穴有42个,其中频次最高的为合谷穴,归经以督脉最多,特定穴以五输穴最多。关联规则分析共筛选出50条。水沟穴施治方法包括针刺、灸法、点刺放血、火针、爪掐(切)、捻(揉)及外治法等,以针刺、灸法为主,刺灸法操作以针三分,留六呼,灸三壮,艾炷如雀粪、小麦大,行泻法最为常见。结论:本研究较为全面地展示了水沟穴在古代临床应用中主治病症、腧穴配伍及临床操作等方面的情况,可为现代临床应用及科研提供借鉴。

铸牢中华民族共同体意识视域下粤北民族古籍研究——基于契约文书的考察

契约文书不仅是粤北地区民族经济活动的直接记录,也是粤北各民族交往交流交融的估证材料。以粤北地区民族古籍中的契约文书作为研究对象,从铸牢中华民族共同体意识视角出发,分析契约文书中所体现的粤北各民族经济往来、法律制度、民族交往、社会变迁等方面信息,以及在形式上集中展现的具有多文风、多语种、多载体特点,从不同的视角和层面客观地载录了中华文化在粤北的形成和发展过程。

激发全社会内生动力和创新活力推进中国式现代化的纲领性文献——对《中共中央关于进一步全面深化改革推进中国式现代化的决定》的解读

《中共中央关于进一步全面深化改革推进中国式现代化的决定》为进一步推进中国式现代化作出了一系列目标明确、科学精准、系统完整、务实管用的重大战略部署,是在新的历史起点上激发全社会内生动力和创新活力,推进中国式现代化的马克思主义纲领性文献。深刻认识新时代以全面深化改革激发全社会内生动力和创新活力推进中国式现代化的重要性和必要性,把握新时代以全面深化改革激发全社会内生动力和创新活力推进中国式现代化的实践逻辑,运用好新时代以全面深化改革激发全社会内生动力和创新活力推进中国式现代化的辩证法则,对于进一步以全面深化改革调动社会各界的主体性、能动性和创造性,激发全社会内生动力和创新活力,推进国家治理体系和治理能力现代化,有着十分重大的理论意义和实践意义。