Other Cities’Distribution Institutions for Publishing Books in Modern Chinese Libraries:Taking Huating Bookstore,the Shanghai General Distribution Office of Modern Zhejiang Library,as an Example

Many modern Chinese libraries have established distribution agencies in other cities to distribute books published or sold on consignment.Huating Bookstore,which was once the Shanghai General Distribution Office of Zhejiang Library in modern times,is one of them.On the basis of a brief description of modern Zhejiang Library and its book publishing,as well as the overview of Huating Bookstore,the paper introduces and analyzes the ZPL Publishing Book Catalogue sent by Huating Bookstore,and the ZPL publishing and selling consignment books issued by Huating Bookstore.It points out that Huating Bookstore is a bridge between the ZPL located in Hangzhou and various retail ZPL publishing bookstores in Shanghai.Their production and sales relationship is a mutually beneficial one.

A U-Shaped Network-Based Grid Tagging Model for Chinese Named Entity Recognition

Chinese named entity recognition(CNER)has received widespread attention as an important task of Chinese information extraction.Most previous research has focused on individually studying flat CNER,overlapped CNER,or discontinuous CNER.However,a unified CNER is often needed in real-world scenarios.Recent studies have shown that grid tagging-based methods based on character-pair relationship classification hold great potential for achieving unified NER.Nevertheless,how to enrich Chinese character-pair grid representations and capture deeper dependencies between character pairs to improve entity recognition performance remains an unresolved challenge.In this study,we enhance the character-pair grid representation by incorporating both local and global information.Significantly,we introduce a new approach by considering the character-pair grid representation matrix as a specialized image,converting the classification of character-pair relationships into a pixel-level semantic segmentation task.We devise a U-shaped network to extract multi-scale and deeper semantic information from the grid image,allowing for a more comprehensive understanding of associative features between character pairs.This approach leads to improved accuracy in predicting their relationships,ultimately enhancing entity recognition performance.We conducted experiments on two public CNER datasets in the biomedical domain,namely CMeEE-V2 and Diakg.The results demonstrate the effectiveness of our approach,which achieves F1-score improvements of 7.29 percentage points and 1.64 percentage points compared to the current state-of-the-art(SOTA)models,respectively.

Chinese micro-blog sentiment classification through a novel hybrid learning model

With the rising and spreading of micro-blog, the sentiment classification of short texts has become a research hotspot. Some methods have been developed in the past decade. However, since the Chinese and English are different in language syntax, semantics and pragmatics, sentiment classification methods that are effective for English twitter may fail on Chinese micro-blog. In addition, the colloquialism and conciseness of short Chinese texts introduces additional challenges to sentiment classification. In this work, a novel hybrid learning model was proposed for sentiment classification of Chinese micro-blogs, which included two stages. In the first stage, emotional scores were calculated over the whole dataset by utilizing an improved Chinese-oriented sentiment dictionary classification method. Data with extremely high or low scores were directly labeled. In the second stage, the remaining data were labeled by using an integrated classification method based on sentiment dictionary, support vector machine(SVM) and k-nearest neighbor(KNN). An improved feature selection method was adopted to enhance the discriminative power of the selected features. The two-stage hybrid framework made the proposed method effective for sentiment classification of Chinese micro-blogs. Experiments on the COAE2014(Chinese Opinion Analysis Evaluation 2014) dataset show that the proposed method outperforms other schemes.

Meteorite classification for building the Chinese Antarctic Meteorite Depository Introduction of the classification of 500 Grove Mountains meteorites

Meteorites provide an important window into the origins and evolution of the solar system. Since the first four meteorites were recovered in Grove Mountains, Antarctica, in 1998, a further total of 12665 meteorites have been collected over seven polar seasons in the Grove Mountains. All of these meteorites are owned and managed by the Chinese Antarctic Meteorite Depository （CAMD） at the Polar Research Institute of China （PRIC）. In recent years, another 500 Antarctic meteorites have been classified and characterized based on mineralogy and petrology. In this work we examine four samples that have been identified as terrestrial, and a further 496 samples that have been confirmed as meteorites. These meteorites are further divided into different types：488 ordinary chondrites, one eucrite, one ureilite, one CM2 carbonaceous chondrite, one EH4 enstatite chondrite, one mesosiderite and three iron meteorites. The classification of meteorites not only provides an abundance of fundamental scientific data, but is also significant for introducing meteorites and related scientific knowledge to the publics particularly via the website of Chinese Resource-sharing Platform of Polar Samples for scientific research and education.

A Study on the Classification and Well-Logging Identification of Eclogite in the Main Hole of Chinese Continental Scientific Drilling Project

Eclogite, one of the important lithologies in the main hole of the Chinese Continental Scientific Drilling （CCSD） Project, exists above the depth of 3 245 m and has distinctive responses of gamma-ray, compensating density and neutron well-logging, and so on. In this study, according to the diversities of minerals and chemical components and well-logging responses, edogites are classified from three aspects of origin, content of oxygen, and sub-mineral. We studied the logging identification method for eclogite sub-classes based on multi-element statistics and reconstructed 11 kinds of eclogite. As a result, eclogites can be divided into 6 types using well logs. In the light of this recognition, the eclogite in the main hole is divided into 20 sections, and the distribution characters of all sub-classes of eclogite are analyzed, which will provide important data for geological research of CCSD.

Hierarchical Classification of Chinese Documents Based on N grams

We explore the techniques of utilizing N gram information to categorize Chinese text documents hierarchically so that the classifier can shake off the burden of large dictionaries and complex segmentation processing, and subsequently be domain and time independent. A hierarchical Chinese text classifier is implemented. Experimental results show that hierarchically classifying Chinese text documents based N grams can achieve satisfactory performance and outperforms the other traditional Chinese text classifiers.

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%.

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.

Classification of Emergency Responses to Fatal Traffic Accidents in Chinese Urban Areas

Fatal traffic accidents in urban areas can adversely affect the urban road traffic system and pose many challenges for urban traffic management.Therefore,it is necessary to first classify emergency responses to such accidents and then handle them quickly and correctly.The aim of this paper is to develop an evaluation index system and to use appropriate methods to investigate emergency-response classifications to fatal traffic accidents in Chinese urban areas.This study used a multilevel hierarchical structural model to determine emergency-response classification.In the model,accident attributes,urban road network vulnerability,and institutional resilience were used as classification criteria.Each evaluation indicator was selected according to importance ranking and independence screening and was given an interpretation and a quantitative criterion.The Fuzzy Delphi Method was used to rank the importance of the evaluation indices and the combined weight of each index was calculated using the G1 method.Finally,the case of a fatal traffic accident was used to validate the model.The results showed that the multilevel hierarchical structural model,Fuzzy Delphi Method,and G1 method can effectively address the problem of emergency-response classification.Because of its simplicity and adaptability,the approach presented here could be useful for decisionmakers and practitioners for determining emergency-response classifications.

Classification and Translation of Chinese Abbreviations

Chinese abbreviation,containing fewer words and delivering a wealth of information,is a vital component of Chinese language.But the tremendous differences between Chinese and English make it an arduous task to translate Chinese abbreviations into English.Based on the analyses of the structure and patterns of word–formation of Chinese abbreviations,it makes a classification of Chinese abbreviations,summarize the translation methods,and point out some attention points in translation.A systematic analysis on the structure and classification of Chinese abbreviations will be beneficial to reduce the mistakes in its translation.

Diagnostic value of traditional Chinese medical dialectical classification in hashimoto's thyroiditis complicated with suspicious nodules

Objective:To explore the diagnostic value of traditional Chinese medical(TCM)dialectical classification in Hashimoto's thyroiditis complicated with suspicious nodules.Methods:The clinical data of patients with Hashimoto's thyroiditis complicated with thyroid nodules in the Department of Breast and thyroid surgery of Weifang Hospital of traditional Chinese Medicine from January 2018 to December 2019 were collected.The patients were examined by 2 or more experienced TCM doctors,and the four diagnostic data were obtained,and then the relevant syndrome types of the patients were judged according to the data.According to the color Doppler ultrasonographic features of thyroid nodules,the patients who met the indication of fine needle aspiration biopsy of thyroid nodules were selected and underwent fine needle aspiration biopsy of thyroid nodules before operation.To analyze the clinical diagnostic value of that the ultrasonic mode used in this study and thyroid cytopathology Bethesda report system combine dialectical classification of traditional Chinese medicine in Hashimoto's thyroiditis complicated with suspected thyroid nodules.Result:A total of 89 patients with Hashimoto's thyroiditis complicated with thyroid nodules were collected.according to the ultrasonic mode,the difference between different modes was statistically significant(P<0.05).The mode of color ultrasound is also related to the dialectical classification of traditional Chinese medicine.The patients with high malignant risk score are mainly qi depression and phlegm stagnation,phlegm and blood stasis,while those with low score are exuberant liver fire and heart liver yin deficiency.According to the study of different The Bethesda System for Reporting Thyroid Cytopathology(TBSRTC)classification,the dialectical classification of patients with higher TBSRTC classification was more inclined to qi depression and phlegm stagnation,phlegm and blood stasis,and there was significant difference between different classification(P<0.05).Conclusion:Qi depression and phlegm obstruction,phlegm and blood stasis have high ultrasound malignant risk score and high TBSRTC classification grade in patients with Hashimoto's thyroiditis complicated with suspected thyroid nodules,which has important clinical diagnostic value.

汉语动词资源馆(Chinese Verb Library)的构建

该研究以动词的语义聚合层次为核心,构建了含有四个语义层级的动词分类系统,依托生成词库理论、语义格框理论和构式语法理论,从事件结构、语义格框架、物性角色、句法格式四个角度来对动词的自身属性以及组合性等特征进行描述,从而构造出能够解释并深入描述动动之间、动名之间甚至是超常搭配用法的汉语动词资源馆Chinese Verb Library(CVL)。实验表明,该研究可以为句法分析、语义角色标注、尤其是揭示隐含的谓间关系提供新的支持。

ON THE STRUCTURES OF RAM-BASED CHINESE CHARACTER LIBRARIES

The Chinese character library is one of the important data structures in the Chinese information Processing system.The behavior of the whole system depends directly on the reasonableness of design for its structure.This paper expounds the structures of RAM-based Chinese character libraries,static and dynamic ,The paper offers a descriptive method for this behavior and inquires into some algorithms related to the structures mentioned above.

The EST Analysis of A Suppressive Subtraction cDNA Library of Chinese Wild Vitis pseudoreticulata Inoculated with Uncinula necator

Uncinula necator is a worldwide serious fungus disease causing annual heavy lost on grapevine production. In order to get more informations on defense related EST sequences and help breeding program, we constructed and characterized a suppression subtractive hybridization cDNA library with artificially inoculated leaves and control Chinese wild Vitis pseudoreticulata clone Baihe-35-1, which is highly resistant to powdery mildew. In the library, the length of 58 EST fragments known as putative functions varied from 130 to 800 bp, and 60% of the ESTs exhibited high similarity to known sequences in database of GenBank with BLASTX analysis. These genes were involved in stress/defense response, detoxification, signal transduction, disease defense, and etc., and 14 ESTs remained unknown or hypothetical proteins, which may be new genes. The experiment provided an important basis for studying the disease-resistance mechanism and obtaining the genes for the aim of improving grapevine powdery mildew resistance.

Discussion of Online Teaching Strategies for Teaching Elementary Chinese Characters to Foreigners Based on Error Analyses

The expanding role of the Chinese language in international communications has become increasingly prominent as China’s comprehensive national power continues to grow,leading to a significant rise in the number of Chinese language learners.Since online teaching is not limited by time and space,its application is widespread.For beginners in the Chinese language,the Chinese characters are both a priority and a challenge.The“Chinese Character Classification,”also known as the“Six Writings,”is the earliest systematic theory of Chinese character structures,and teaching Chinese characters in categories based on the“Chinese Character Classification”is a method that fits the cognition of beginners.In order to teach Chinese characters in a targeted approach,based on the collection and analysis of the common errors of Chinese characters among beginners,(1)this paper proposes that(a)the intuitive method can be applied to teach pictographic characters,indicative characters,and associative compound characters in online teaching;(b)the inductive-deductive method of“basic characters to new characters”can be applied for the teaching of pictophonetic characters and associative compound characters;(c)the learning of character patterns should be approached in a whole-part-whole process,while importance should be attached to the suggestion of the frequency effect with a view to facilitating the online learning of Chinese characters for beginners.The aim of this paper is to provide some practical implications for the online teaching of Chinese characters to foreigners.

A 4-Corner Codes Classifier Based on Decision Tree Inductive Learning for Handwritten Chinese Characters

The classification for handwritten Chinese character recognition can be viewed as a transformation in discrete vector space. In this paper, from the point of discrete vector space transformation, a new 4-corner codes classifier based on decision tree inductive learning algorithm ID3 for handwritten Chinese characters is presented. With a feature extraction controller, the classifier can reduce the number of extracted features and accelerate classification speed. Experimental results show that the 4-corner codes classifier performs well on both recognition accuracy and speed.

Journal of the Chinese Library Association and Modern Chinese Library Cause

Journal of the Chinese Library Association is an agency publication of the Chinese Library Association.Its purpose is to promote the exchange of library science,the popularization of library science knowledge,and the development of library undertakings.The journal has numerous columns,rich content,long publication time and wide distribution,laying an important foundation for the innovation,transformation and development of modern library cause.

An overview on the development of Chinese library and information science journals

This paper gives an overview of the history and the present status of Chinese library and information science journals, and introduces the operation and management of Chinese library and information science journals by taking Journal of Library Science In China, Library and Information Service, Journal of Academic Libraries, and Journal of Information Science as examples. Besides, six suggestions are given for the future development of Chinese library and information science journals.

Library science education and the competitiveness of its graduates:A survey and an analysis of Chinese library directors' perceptions

These authors have made a sampling survey of professional qualifications of library directors of various types of libraries in China.The subject coverage of this survey includes but not limited to the pattern of library position distribution and work conditions of those library science degree holders.It also studies such matters as the occupational roles of library science graduates in the library,the influencing factors of their professional competency(as it is perceived by library directors),library directors' opinion about the core curriculum of library science educational programs,etc.On the basis of this survey result and analysis,these authors attempt to show how Chinese librarians' professional competency can be identified and nurtured to a higher level of attainment.

Chinese Astronomers Created an Empirical Stellar Spectra Library from LAMOST

Astronomers from the National Astronomical Observatories of Chinese Academy of Sciences(NAOC) present an empirical stellar spectra library created with spectra from the LAMOST Data Release 5 (DR5). This library represents a uniform data set and covers a wide span of parameter space.