The paper introduces the background and motivation of Named Entity Recognition，and summarizes the history development of Named Entity Recognition at home and abroad, as well as the related technology and evaluation method. Finally，it discusses the new development trends on Named Entity Recognition.

[Objective] This paper discusses the mechanism of User Profiles construction process from the perspectives of design thinking and data types. [Coverage] We used Google Scholar and CNKI to search literatures with the keywords “User Personas” and “User Profiles”. Then we selected 90 representative literatures on User Personas in conjunction with topic screening, intensive reading and retrospective method. [Methods] Firstly, this paper studies the construction process of User Profiles from the perspective of design thinking, specifically combining the four perspectives of Goal-Directed, Role-Based, Engagement-Based and Fiction-Based. Second, it analyzes construction process of User Profiles from the perspective of data types, specifically combining Ontology or Concept, Subject or Topic, Interest or Preference, Behavior or Log, Multidimension or Fusion. Next, the construction methods are compared in detail from three aspects: logical ideas, performance characteristics and limitations. Finally, the next step for research on User Profiles is prospected. [Results] User Profiles technology plays a vital role in many areas such as online public opinion governance, advertising marketing and personalized services. [Limitations] There is no in-depth analysis of the evaluation indicators of User Profiles algorithms. [Conclusions] Although the existing methods of User Profiles can meet the needs of many applications to a certain extent, in the era of big data, it still faces the challenges of data sparsity, scene intelligence perception and user interest migration.

After reviewing the expert system s benefits to cataloguing and. the related research works abroad,we analyze the characteristics of title pages and copyright pages of Chinese books, the main sources of biblio- graphic data, in the light of linguistics and layout, and present the results of a feasibility study of automatic cataloguing for Chinese books. Four kinds of system models, then, are put forward according to the different requirements of various libraries. In the end, we discuss the technical matter involved in development of expert cataloguing system for Chinese books.

[Objective]This paper aims to explore new content-based technology to retrieve and display 3D models, and expands the services of institutional repository. [Methods] First, we modified the open source 3D model retrieval algorithm created by the Taiwan University. Second, we obtained the orthogonal projection and features of the 3D models with the off-screen rendering technique. Finally, we used Java3D technique to generate the thumbnails of the 3D models, and then presented them online with the help of Three.js. [Results] We could retrieve 3D models from the institutional repository by submitting their URLs or the uploading methods. User could also use mouse to rotate or zoom in/out the 3D models while browsing them online. [Limitations] The proposed 3D model retrieval technique met needs of the institutional repositories. However, the recall and precision of the new system could to be improved with the help of the latest techniques in 3D model retrieval. [Conclusions] The proposed method helps the CSpace system manage 3D model collections effectively, which provides more options to retrieve and use the 3D models.

This paper firstly analyzes the relation between search engine evaluation and usability analysis. Based on the characteristics of the three stages of information retrieval by search engine, the demand of usability evaluation is given,and the evaluation hierarchical model on the usability of search engine is constructed based on the four foundations for the choice of evaluation indicators. Then the weights of indicators are accounted by Delphi method,and a valuable search engine usability evaluation system is provided.

This paper describes Shanghai Library computer management system.It also introduces the structure of its computer system and network system,the feature and reliability of the system,and seven application subsystems.

Ancient rare books are the documents for which there exists maximal contradiction between their usage and preservation while the best way is to digitize them.The fulltext data entering should keep the original appearance of the rare books.The Chinese Ancient Rare Books Image Retrieval System produced by the Shanghai Library can transfer the fulltext data into CD ROMs as images and the functions of the indexing,searching and browsing as well ,which serves as a good attempt to digitize the ancient rare books.

本文从论述中文文献单字标引的优缺点出发，提出了两种改进措施。经改进后的单字标引系统既可保持原有系统的优点，又解决了它原有的不足之处。

This paper introduces the development of the networks structure,scale,application system and information resource of China Engineering Technology Information Networks,summarizing the characteristics and problems in its building,and describing its prospects.

This paper reviews the lilerature on automatic abstracting,introducts an automatic system of summarizing text by sen tence selection,details implications of its results,and points out that the method of summarizing text is still usefull for automatic condensation of text.

[Objective] This paper analyzes and summarizes the current situation of the development of text sentiment in financial markets, and provides reference for subsequent related research. [Coverage] We used “financial market”, “text sentiment analysis”, “text sentiment” and “investor sentiment” as keywords to search on academic platforms such as CNKI, Web of Science and Google Academic, and extended the search for relevant literatures. A total of 115 papers were reviewed. [Methods] We classified the extracted text sentiment according to the type of the source financial text, then introduced the framework of text sentiment analysis, and finally sorted out the relevant research results on the impact of text sentiment on the financial markets. [Results] Text sentiment in financial markets can be divided into information reporting sentiment, news media sentiment and social media sentiment. In the construction of sentiment indicators, dictionary-based methods and machine learning-based methods are widely used. The above three text sentiments have a certain impact on the financial markets. [Limitations] Due to the universality of text analysis methods in various fields, the selected literature on the framework of text sentiment analysis is not entirely focused on the financial markets. [Conclusions] When constructing financial text sentiment indicators, we should choose the appropriate sentiment analysis method according to the text characteristics, research conditions and research objectives.

[Objective] This paper investigates recent researches addressing sentiment analysis on social media.[Coverage] 163 papers in total are collected and 91 articles are cited for this review, covering articles subject on social media and sentiment analysis retrieved from Web of Science Core Collection during 2015-2019, and a supplement from citation analysis and browsing.[Methods] Content analysis is used for exploring task, technology, and application of sentiment analysis on social media.[Results] A variety of sentiment analysis tasks are summarized, refine sentiment analysis techniques on social media platforms are clarified, application fields are discussed as well.[Limitations] There is no in-depth analysis of the step and procedure for the sentiment analysis algorithm.[Conclusions] The findings provide an overview of sentiment analysis study, including the state-of-the-art technique, application and challenges on social media platforms.

[Objective] Integrate open source file-format identification tool into Digital Preservation System (DPS) to get complex object format information. [Context] Based on the existing open source tools, to meet the practical requirements, the DPS needs choose appropriate tools for application integration. [Methods] Analyze and compare several open source file-format identification tools. According to the practical requirements, DROID has been chosen for the DPS. At the same time to meet the efficiency requirements of DPS, an idea of choosing DROID batch format identification of complex objects is proposed. [Results] Batch format processing module which is integrated with DROID is utilized to complete format identification of complex objects and technical metadata extraction. [Conclusions] DROID is an excellent open source tool, of which the automatic batch processing can meet the requirements of DPS.

The Documentution & Information Centre of the Chinese academy of Scienecs The Study takes a user-focused approach to analyzing data requirement. It uses an entity analysis technique to finding the key objects of interest to users of bibliographic records, and then identifies the characteristics or attributes and the relationships between entities. The aim of study was to produce a clearly defined, structured framework, and to recommend a basic level of functionality for records created by national bibliographic agencies.

[Objective] This paper analyzes and summarizes the main optimization methods of the BERT language representation model released by Google to provide reference for future studies based on BERT. [Coverage] A total of 41 main literatureor models related to optimization of BERT have been reviewed and analyzed. [Methods] The optimization routes were explained from four aspects: pre-training targets optimization, external knowledge base fusion, Transformer structure evolution and pre-training model compression. [Results] The optimization of pre-training targets and the improvement of Transformer structure caught the earliest attention by researchers, and became the main routes to optimize BERT. After that, the pre-training model compression and the integration of external knowledge bases have also become new directions of research. [Limitations] Research on BERT has developed extremely rapidly, and some of the related research work may not yet be covered. [Conclusions] Researchers can focus on pre-training targets optimization and Transformer structure improvement, and consider choosing the optimization routes according to different application scenarios.

[Objective] A new service cloud which supports on-demand self-service is built for monitoring strategic S&T information. [Context] Based on the existing automatic Web information monitoring system, the system need extend to support more information analysts. [Methods]With regard to the problems of scalability and flexibility of the existing system, an idea of building a new service cloud is proposed, the service cloud with focusing on six aspects of the problems is designed and implemented. [Results] The service cloud for strategic S&T information monitoring with the characters of scalability and flexibility is implemented and now is used by more users. [Conclusions]Implementation of the service cloud results in an on-demand self-service model for user. The new platform supports more information analysts and provides more effective service for information analysts.

This paper describes a large computer networking project,called NCFC (The national Computing and networking Facility of China) including its construct,operations and usage .It also gives a brief introduction about Internet which is the largest computer network in the world. And NCFC had connected into Internet.Finally,the author gives some ideas about building China Internet.

[Objective] This paper summarizes the evolution and application of attention mechanism in natural language processing.[Coverage] We searched “attention” with the title/topic fields of WoS, ACM Digital Library, arXiv and CNKI from January 2015 to October 2019. Then, we manually screened the topic literature in the field of natural language processing, and obtained 68 related papers.[Methods] We first summarized the general attention mechanism, and sorted out its derivations. Second, we thoroughly reviewed their applications in natural language processing tasks.[Results] The application of attention mechanism in natural language processing focused on sequence labeling, text classification, reasoning and generative tasks. There were adaptation rules between tasks and the various attention mechanisms.[Limitations] Some adaptations between the mechanisms and the tasks were obtained from the overall performance of the model. More research is needed to examine the performance of different mechanisms.[Conclusions] The study of attention mechanism has effectively promoted the development of natural language processing. However, the mechanism of action is not yet clear. Future research should focus on making attention mechanism closer to those of the human beings.

[Objective] This paper reviews literature on text sentiment analysis, aiming to summarize its technical development trends and applications. [Coverage] We searched relevant literature from the Web of Science Core Collection and CNKI database on the concepts, methods and techniques of sentiment analysis. A total of 69 papers were retrieved from 2011 to 2020 and then analyzed. [Methods] We summarized the main models and applications of text sentiment analysis from the dimensions of time and theme. We also discussed the fields needs to be improved. [Results] There were mainly three methods for text sentiment analysis, which were based on sentiment lexicon and rules, machine learning, as well as deep learning. Each method has advantages and disadvantages. The methods based on multi-strategy hybrid became more popular in recent years. [Limitations] We reviewed previous literature on text sentiment analysis from the perspective of macro-technical methods. More research is needed to compare and elaborate the technical details of sentiment analysis algorithms. [Conclusions] The development of artificial intelligence technology (big data and deep learning) will further improve text sentiment analysis, and benefit business decision making applications.

This paper introduces the concepts and origins of Technology Readiness Levels(TRL) briefly and distinguishes TRL from related concepts, like technology life cycle. Then, much emphasis is put on the widely adopted NASA TRL system, and its characteristics description and research framework, as well as its applied values, assessment tools and limitation of applications are also described. At the end, two methods, including latent semantic indexing and co-word analysis, are carefully examined on the probability of identification of TRLs.

This paper studies the visualization method of patent family which is transformed into tree structure,then puts formard two visualization methods including country mode and priority mode.Then a patent family visualization system is designed and implemented,and its technical idea,basic framework,main functions and key technologies are elaborated.At last, an empirical illustration about Apple's touch screen patent is proposed.

 In view of the shortcomings of traditional methods for analyzing public opinions, this paper proposes a new idea of public opinion analysis under the Web,and then designs a model for it. Experiments show that the proposed model is an effective solution to analyzing public opinion under the Web.

[Objective] Based on the traditional financial data analysis, this paper explores the impacts of online news on stock market, aiming to improve the accuracy of predicting stock trends. [Methods] First, we used the Convolutional Neural Network (CNN) and Bi-directional Long Short-Term Memory (Bi-LSTM) to extract news events and their sentiment orientations. Then, we proposed a prediction model for stock trends, which combines the stock numerical data and the news event sentiments. Finally, we examined the feasibility of this model with two individual stocks (GREE Electric Appliance in the household appliance industry and ZTE in the electronic appliance industry). [Results] The prediction accuracy of our model was 11.6% and 25.6% higher than the exiting algorithms. [Limitations] We did not evaluate the impacts of prediction period on the performance of the proposed model. [Conclusions] The news events and their sentiment orientations could lead to the fluctuation of stock prices.

本文提出九十年代我国计算机情报检索和相关技术的发展目标，主要包括实现以情报、计算机、通信三者结合为主体的全面科技情报服务，实现情报过程和业务的全面自动化，建立以现代化情报技术为主要手段，并具有一定自我发展能力的采集、组织和传播信息的新型情报行业，围绕这些目标提出二个方面的主要任务和课题。

This paper introduces what the advantages of Altmetrics that by using the social network usage data to recommend the information retrieval ranking order and with the other impact index to change the scholar evaluation approach. By using the case observation analysis, the author draws-up the open data framework of the Altmetrics.com, focuses on its specialized service for the Article-Level Metrics. For discussion on the library new knowledge service issue in the open repository, open publishing supporting and the new research-group-embed information service, the two core articles which can improve the empirical validation method are simplified as a brief operational workflow.

[Objective] In order to keep the fidelity of digital information resources in libraries, museums and archives during the process of copyright protection.[Methods] The zero-watermarking scheme based on block compressive sensing and Arnold transformation is proposed. The proposed scheme uses important features of original image and the meaningful copyright information to construct zero watermark. [Results] The acquired zero watermark has good discrimination. Also, this scheme possesses the robust ability to resist on image-manipulation attacks under consideration. [Limitations] Since the subjects in this study are gray level images, there are some limitations. [Conclusions] The optimized scheme using block compressive sensing, in a manner, contributes to the copyright protection of digital information resources in libraries, museums and archives.

A technique for converting Library of Congress Subject Headings MARCXML to Simple Knowledge Organization System (SKOS) RDF is described. Strengths of the SKOS vocabulary are highlighted, as well as possible points for extension, and the integration of other semantic web vocabularies such as Dublin Core. An application for making the vocabulary available as linked data on the Web is also described.

[Objective] This paper aims to summarize spatio-temporal data modeling methods to provide a theoretical basis for the study of the organization and management of space-time knowledge. [Coverage] Literature search was conducted using the “spatial-temporal data model” and “spatio-temporal data model”, respectively, within a limited time frame and journal type, in Baidu Academic, Google Scholar, CNKI, and Engineering Village. Some relevant documents were obtained and screened according to the degree of relevance of the research topic. Finally we chose 64 related documents to review. [Methods] The spatio-temporal data model is classified according to the level of abstraction of the modeled objects, and the related researches on the spatio-temporal data model are summarized from three levels of the physical layer, logic layer and application layer. [Results] In recent years, the studies of the spatio-temporal data model in the physical layer mainly focused on the revision of the previous model. The spatio-temporal data models of the application layer focused on satisfying the specific needs of various fields. However, the researches on the logic layer need to be improved in terms of expression ability. [Limitations] There are few horizontal comparison studies of spatial-temporal data models at different levels. [Conclusions] Large-scale space-time information management and utilization will provide broad space for development of space-time data modeling in the future.

[Objective] This paper teases out the research context of cross-lingual sentiment analysis (CLSA). [Coverage] We searched “TS=cross lingual sentiment OR cross lingual word embedding” in Web of Science database and 90 representative papers were chosen for this review. [Methods] We elaborated the following CLSA methods in detail: (1) The early main methods of CLSA, including those based on machine translation and its improved variants, parallel corpora or bilingual sentiment lexicon; (2) CLSA based on cross-lingual word embedding; (3) CLSA based on Multi-BERT and other pre-trained models. [Results] We analyzed their main ideas, methodologies, shortcomings, etc., and attempted to reach a conclusion on the coverage of languages, datasets and their performance. It is found that although pre-trained models such as Multi-BERT have achieved good performance in zero-shot cross-lingual sentiment analysis, some challenges like language sensitivity still exist. Early CLSA methods still have some inspirations for existing researches. [Limitations] Some CLSA models are mixed models and they are classified according to the main methods. [Conclusions] We look into the future development of CLSA and the challenges facing the research area. With in-depth research of pre-trained models on multi-lingual semantics, CLSA models fit for more and wider languages will be the future direction.

The paper introduces the major general Ontology libraries in domestic and foreign: WordNet、DBpedia、Cyc and HowNet, and the successful professional domain Ontology libraries: Biomedical Ontology and Enterprise Ontology. Then it separately compares and analyzes them from five aspects as the description language, storage mode, query language, platform building and application to provide assistance for the study in Ontology library and its application.

建立在数学基础上的情报检索模型，随着人们对情报检索实质认识的深入而不断深化的。本文对已建立的布尔检索、向量检索、概率检索及模糊检索等数学模型用统一的数学模型进行定义，并对它作了综合比较和评价，揭示了情报检索模型的演变过程。

Aiming at the problem of sentiment analysis of incomplete product reviews data, this paper proposes a cross-domain sentiment analysis method based on spectral clustering and transfer learning. With the help of domain-independent words as a bridge, using spectral clustering algorithm to align domain-specific words from different domains into unified clusters, it can reduce the gap between domain-specific words of the two domains, and can improve the accuracy of sentiment classifiers in the target domain. Experiments studies are carried out to show the efficiency and superiority of the proposed approach in solving the problem of cross-domain sentiment analysis of product reviews.

[Objective] As the core content and the important part of patent documents, the extraction task of patent terms is regarded as the basis of research works on the patent. [Methods] A hierarchical filtering method is presented to extract terms. Based on the suffix array, this method takes repeated strings as the candidate words and divides invalid strings into three classes, including the broken string, the redundant string and the common word, according to their features in the candidate set. Besides, by removing the above invalid strings, patent terms are obtained. The authors propose an independence calculation method, a relative activity calculation method and a word segmentation error correction method to filter broken strings and redundant strings respectively. [Results] Experimental results show that the proposed method has a good effect on Chinese patent term extraction. The average precision is 90.54% and the average recall is 87.33%. [Limitations] The method is just suitable for repeated strings and cannot identify the term which frequency number is 1. [Conclusions] The method is effective in patent term extraction.

[Objective] This paper aims to identify the interdisciplinary subjects based on the feature measure method and the PhraseLDA model. [Methods] First, we analyzed the subjects’ interdisciplinary characteristics and constructed their measurement index system. Then, we identified the interdisciplinary subjects with the help of the PhraseLDA model. Finally, we conducted an empirical study of nanotechnology applications in agricultural environments. [Results] A total of 24 cross-topic were objectively identified, including catalyst preparation, soil bioremediation, and many more. Compared with the traditional identification method, the cross-topic recognition rate of the proposed method increased by 71.40%, and the recognition rate of fine-grained topics increased by 42.86%. [Limitations] The number of topics and interdisciplinary topic identification indicators of the PhraseLDA topic model were decided after repeating calculation and debugging. Therefore, the proposed method depends on the rationality of the relevant thresholds. [Conclusions] The proposed method can effectively identify interdisciplinary topics and support scientific decision-making and technological innovation research in related fields.

[Objective] This study builds a prediction model for drugs’ ADMET properties (Absorption, Distribution, Metabolism, Excretion, Toxicity), aiming to evaluate drugs in virtual screening. [Methods] We constructed a drug ADMET prediction based on the Graph Attention Network (GAN). Then, we used the drug ADMET properties from open access databases and scientific publications to create their molecular graphs and structures. Finally, we compared the GAN-based model with three machine learning models and two graph neural network models. [Results] We collected 9 datasets with 149 457 ADMET records. The proposed prediction model had an average accuracy of 0.825 and an average F1-Score of 0.672 with the 9 datasets, which were 6.4% and 26.0% higher than those of the baseline models. [Limitations] The data cleansing process needs to be refined, while the prediction performance can be further improved with a pre-training architecture. [Conclusions] The proposed model could effectively predict a drug’s ADMET, which could help virtual drug screening and computer-aided drug developments.

The artical first analysed the characteristics of computerized citation system,then discussed some technical matters related to its design,such as the f unctions of this kind of system,the selection of programming languages,the data sturucture and so on.

This paper describes the generation,concepts,basic features,and the models of a digital library.The authors,especially,present that a dream of the electronic library is able to come true under Internet environment,and a real electronic library model consists of four structure levels which are user interfaces,networks and communications,information resource,and reference service system. There are five functions in the digital library which are digitized documents for various media,storage,access,transmission, privilege and management.The authors are planning to create an embryonic form of a digital library in Shanghai Jiantong University.