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.

A Study on the Correlation Between LIWC Word Categories and Chinese Composition Writing Performance of Fourth,Fifth,and Sixth Grade Students

This study focuses on the analysis of the Chinese composition writing performance of fourth,fifth,and sixth grade students in 16 selected schools in Longhua District,Shenzhen during the spring semester of 2023.Using LIWC(Linguistic Inquiry and Word Count)as a text analysis tool,the study explores the impact of LIWC categories on writing performance which is scaled by score.The results show that the simple LIWC word categories have a significant positive influence on the composition scores of lower-grade students;while complex LIWC word categories have a significant negative influence on the composition scores of lower-grade students but a significant positive influence on the composition scores of higher-grade students.Process word categories have a positive influence on the composition scores of all three grades,but the impact of complex process word categories increases as the grade level rises.

An Optimized Chinese Filtering Model Using Value Scale Extended Text Vector

With the development of Internet technology,the explosive growth of Internet information presentation has led to difficulty in filtering effective information.Finding a model with high accuracy for text classification has become a critical problem to be solved by text filtering,especially for Chinese texts.This paper selected the manually calibrated Douban movie website comment data for research.First,a text filtering model based on the BP neural network has been built;Second,based on the Term Frequency-Inverse Document Frequency(TF-IDF)vector space model and the doc2vec method,the text word frequency vector and the text semantic vector were obtained respectively,and the text word frequency vector was linearly reduced by the Principal Component Analysis(PCA)method.Third,the text word frequency vector after dimensionality reduction and the text semantic vector were combined,add the text value degree,and the text synthesis vector was constructed.Experiments show that the model combined with text word frequency vector degree after dimensionality reduction,text semantic vector,and text value has reached the highest accuracy of 84.67%.

Parallel naive Bayes algorithm for large-scale Chinese text classification based on spark

The sharp increase of the amount of Internet Chinese text data has significantly prolonged the processing time of classification on these data.In order to solve this problem,this paper proposes and implements a parallel naive Bayes algorithm(PNBA)for Chinese text classification based on Spark,a parallel memory computing platform for big data.This algorithm has implemented parallel operation throughout the entire training and prediction process of naive Bayes classifier mainly by adopting the programming model of resilient distributed datasets(RDD).For comparison,a PNBA based on Hadoop is also implemented.The test results show that in the same computing environment and for the same text sets,the Spark PNBA is obviously superior to the Hadoop PNBA in terms of key indicators such as speedup ratio and scalability.Therefore,Spark-based parallel algorithms can better meet the requirement of large-scale Chinese text data mining.

Topic-Aware Abstractive Summarization Based on Heterogeneous Graph Attention Networks for Chinese Complaint Reports

Automatic text summarization(ATS)plays a significant role in Natural Language Processing(NLP).Abstractive summarization produces summaries by identifying and compressing the most important information in a document.However,there are only relatively several comprehensively evaluated abstractive summarization models that work well for specific types of reports due to their unstructured and oral language text characteristics.In particular,Chinese complaint reports,generated by urban complainers and collected by government employees,describe existing resident problems in daily life.Meanwhile,the reflected problems are required to respond speedily.Therefore,automatic summarization tasks for these reports have been developed.However,similar to traditional summarization models,the generated summaries still exist problems of informativeness and conciseness.To address these issues and generate suitably informative and less redundant summaries,a topic-based abstractive summarization method is proposed to obtain global and local features.Additionally,a heterogeneous graph of the original document is constructed using word-level and topic-level features.Experiments and analyses on public review datasets(Yelp and Amazon)and our constructed dataset(Chinese complaint reports)show that the proposed framework effectively improves the performance of the abstractive summarization model for Chinese complaint reports.

Interdiscursivity and Promotional Discourse:A Corpus-Assisted Genre Analysis of About Us Texts on Chinese University Websites

The debate on the marketization of discourse in higher education has sparked and sustained interest among researchers in discourse and education studies across a diversity of contexts.While most research in this line has focused on marketized discourses such as advertisements,little attention has been paid to promotional discourse in public institutions such as the About us texts on Chinese university websites.The goal of the present study is twofold:first,to describe the generic features of the university About us texts in China;and second,to analyze how promotional discourse is interdiscursively incorporated in the discourse by referring to the broader sociopolitical context.Findings have indicated five main moves:giving an overview,stressing historical status,displaying strengths,pledging political and ideological allegiance,and communicating goals and visions.Move 3,displaying strengths,has the greatest amount of information and can be further divided into six sub-moves which presents information on campus facilities,faculty team,talent cultivation,disciplinary fields construction,academic research,and international exchange.The main linguistic and rhetorical strategies used in these moves are analyzed and discussed.

Intercultural Communication and Chinese Tourism Texts Translation

Intercultural communication language plays a crucial role in our global tourism.When we are doing translation we are doing intercultural communication in a sense,so it is necessary for translators to have intercultural communication awareness and be sensitive to the cultural elements in translation.Taking the perspective of intercultural communication,this paper analyses the cultural elements in Chinese tourism material translation in terms of culturally-loaded words and terms,and presents certain translation techniques a translator can use to deal with culturally-loaded words in their translation.

Chinese News Text Classification Based on Convolutional Neural Network

With the explosive growth of Internet text information,the task of text classification is more important.As a part of text classification,Chinese news text classification also plays an important role.In public security work,public opinion news classification is an important topic.Effective and accurate classification of public opinion news is a necessary prerequisite for relevant departments to grasp the situation of public opinion and control the trend of public opinion in time.This paper introduces a combinedconvolutional neural network text classification model based on word2vec and improved TF-IDF:firstly,the word vector is trained through word2vec model,then the weight of each word is calculated by using the improved TFIDF algorithm based on class frequency variance,and the word vector and weight are combined to construct the text vector representation.Finally,the combined-convolutional neural network is used to train and test the Thucnews data set.The results show that the classification effect of this model is better than the traditional Text-RNN model,the traditional Text-CNN model and word2vec-CNN model.The test accuracy is 97.56%,the accuracy rate is 97%,the recall rate is 97%,and the F1-score is 97%.

The Research of Chinese Text Proofreading Algorithm

Generally, text proofreading consists of two procedures, finding the wrongly used words and then presenting the correct forms. At present, most of the Chinese text proofreading focuses on finding the wrongly used words, but pays less attention to correcting these errors. In this paper, the Chinese text features are interpreted first and then a Chinese text proofreading method and its algorithm are introduced. In this algorithm, text features, including text statistical feature and language structure feature, are properly used. Here, correcting errors goes on at the same time with finding errors. Experimental results show that this method has a performance of detecting 75% of wrongly used Chinese words and correcting about 60% of them with the first candidates.

Construction of Complex Intervention in Traditional Chinese Medicine (TCM): A Preliminary Methodological Study Based on Text Mining and Interviewing Method

Aim: To explore and analyze the feasibility of establishing a program of complex intervention in Traditional Chinese Medicine (TCM) based on Text Mining and Interviewing method. Methods: According to MRC, Constructing the program of complex intervention in TCM by Text Mining and Interviewing method should include 4 steps: 1) establishment of interview framework via normalization of extraction of ancient documents and Effectiveness of collection of modern periodical literatures;2) materialization of interview outline based on Focus Group Interview;3) rudimentary construction of complex intervention program based on Semi-structured Interview;4) evaluation of curative effect of complex intervention. Conclusions: It is feasible and significative to establish a program of complex intervention in TCM based on Text Mining and Interviewing method.

Digital Rights Management for a Chinese XML Text Centre

The Electronic Text Centre of the OpenUniversity of Hong Kong(OUHK)has been in full operationsince early 2001.It currently houses 7,300+electronictexts,including free electronic titles,electronic titlespurchased directly from the market,and about,1,000 locallyproduced electronic titles.The locally produced titles are notavailable in the market but require local digitization andnegotiation with publishers with regard to the right to use(RTU)them so as to meet the learning needs of the OUHKcommunity.Nearl...

Treatment Principles of Obesity with Chinese Herbal Medicine: Literature Analysis by Text Mining

Obesity represents a social health problem worldwide, associated with serious health risks and increased mortality. The prevalence of obesity is reported to be increasing in both developed and developing countries. Obesity is associated with a significant range of comorbidities and is linked with increases in mortality, thus the treatment of obesity is very important. Chinese herbal medicine (CHM) has been used for weight management both in China and in western countries for many years, the effectiveness and safety of CHMs in obesity have been proved. Yet the principles of treating obesity with CHMs are hard to manage due to the complexity of TCM theory. In this study, a novel text mining method was developed based on a comprehensive collection of literatures in order to explore the treatment principles more intuitively. Networks of TCM patterns and CHMs which are most frequently used in obesity treatment are built-up and analyzed, two major principles are explored in treating obesity: one is resolving phlegm and dampness, the other is clearing heat and reinforcing deficiency. These findings might guide the clinicians in treatment of obesity.

The Chinese Image on Twitter： An Empirical Study Based on Text Mining

The study use crawler to get 842,917 hot tweets written in English with keyword Chinese or China. Topic modeling and sentiment analysis are used to explore the tweets. Thirty topics are extracted. Overall, 33% of the tweets relate to politics, and 20% relate to economy, 21% relate to culture, and 26% relate to society. Regarding the polarity, 55% of the tweets are positive, 31% are negative and the other 14% are neutral. There are only 25.3% of the tweets with obvious sentiment, most of them are joy.

The Silk Road (丝绸之路) and Sources of Chinese Medicine Expansion:Part 4 – Miscellaneous Texts

Medical works and histories provide a general understanding of foreign influence on Chinese medicine,but a variety of miscellaneous texts give a deeper understanding of the details of this interaction.Trade manuals,notes on foreign interactions,archeological discoveries,and religious works all fill in important details on the incorporation of foreign medicines and ideas into Chinese medicine.

Communication Strategies for Chinese Documentaries from High-context to Low-context Culture: A Comparative Study of “Wild China” of BBC and CCTV Version

As an important means of cultural transmission,documentaries are a powerful tool to make known the five thousand years of Chinese civilization to people all over the world.The“Wild China”of BBC version,popular among the great majority of overseas audience,serves as a successful carrier of Chinese culture export.Based on the theory of low-context and high-context culture,this paper uses the method of text analysis and focuses on the study of the texts in the Chinese and English versions of“Wild China”and explores the differences in the texts in terms of content and rhythm.The purpose of this study is to avoid cultural misunderstanding and optimize communication effect.Findings of this study show that against the background of low-context(English)and high-context(Chinese)culture,the English version has a good sense of rhythm,uses rhetoric for vivid description,expresses ideas directly,and provides explanation for phenomena through narrating or telling a story.But Chinese version has plainer descriptions,uses more euphemistic or abstract words,analyzes phenomena in less detail and narrates more formally.So,it is suggested that in translating texts into English,concepts need to be made accessible,logical and direct with more explanation,more rhetoric,more objective evaluation,and less pursuit of artistic abstraction.These communication strategies conforming to low-context culture can help overseas audience accept Chinese culture more easily.

Study on the Textual Coherence Function of Conjunctions in Political Texts and Their Translation Reconstruction

The assessment of translation quality in political texts is primarily based on achieving effective communication.Throughout the translation process,it is essential to not only accurately convey the original content but also effectively transform the structural mechanisms of the source language.In the translation reconstruction of political texts,various textual cohesion methods are often employed,with conjunctions serving as a primary means for semantic coherence within text units.

CTSF:An End-to-End Efficient Neural Network for Chinese Text with Skeleton Feature

The past decade has seen the rapid development of text detection based on deep learning.However,current methods of Chinese character detection and recognition have proven to be poor.The accuracy of segmenting text boxes in natural scenes is not impressive.The reasons for this strait can be summarized into two points:the complexity of natural scenes and numerous types of Chinese characters.In response to these problems,we proposed a lightweight neural network architecture named CTSF.It consists of two modules,one is a text detection network that combines CTPN and the image feature extraction modules of PVANet,named CDSE.The other is a literacy network based on spatial pyramid pool and fusion of Chinese character skeleton features named SPPCNN-SF,so as to realize the text detection and recognition,respectively.Our model performs much better than the original model on ICDAR2011 and ICDAR2013(achieved 85%and 88%F-measures)and enhanced the processing speed in training phase.In addition,our method achieves extremely performance on three Chinese datasets,with accuracy of 95.12%,95.56%and 96.01%.

Chinese English Learners＇ Text Reading Strategy Research

Reading strategies are different from identifying the words, but a kind of metacognitive activity based on the monitoring mode. This paper will explore Chinese English learners＇ text reading strategies according to the cognitive process of the reading, hoping for providing some suggestions and references for Chinese college students to learn English well and improve the text reading ability.

On Translation of Classical Chinese Literary Texts

Chinese classical literature is precious treasure of the world literature. In order to transmit and carry forward it, translation is an effective and necessary way, especially as the development ofglobalization and China＇s economy. This paper mainly discusses the history, difficulties, ways and skills on translation of classical Chinese literary texts in this paper.

English Translation Study of Chinese Tourism Texts Based on the Skopos Theory--A Case Study of Hubei Scenic-spot Translation

Nowadays, China has witnessed vigorous development in tourism industry, and it has made a great contribution to Chinese economic growth. In order to draw more foreign tourists and demonstrate the unique charm and cultural deposits of Chinese landscapes, the translators should capitalize on appropriate translation methods so as to guarantee the translation quality.The thesis analyzes the guiding role of Skopos Theory in tourism texts with a lot of examples, taking the Hubei scenic-spot translation as a carrier, which has important guiding significanse to translators.