Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] The paper explores the construction of literature intelligence big data knowledge resource system, which supports multi-domain intelligent knowledge service.[Method/process] Based on the AI application requirements, drawing on the industry experience, combing the problems of existing resource system, the paper expanded the resource system from multi-level and multi-dimensional, built a reliable data processing process and computing platform to support efficient data collection and processing, and developed intelligent data governance tools to achieve effective governance of knowledge resources and ensure the provision of high-quality data resources.[Result/conclusion] It has initially formed a knowledge resource system covering multiple types and disciplines of sci-tech literature, constructed and completed a highly automated data collection and governance process, implemented multiple data quality control, and accumulated hundreds of millions of high-quality data. At present, it has provided data support for multiple knowledge services.
Subjects: Other Disciplines >> Synthetic discipline submitted time 2023-03-31 Cooperative journals: 《农业图书情报学报》
Abstract： [Purpose/Significance] Scientific and technical (S&T) literature data resources are characterized with wide coverage, large quantity, many types, fast update and strong timeliness. In order to improve the effect and security of S&T literature data management, this paper studies the S&T literature management system based on the data life cycle model. [Method/Process] This paper explores the management mode of S&T documents, constructs the life cycle system of S&T documents based on the data management process, and expounds the data management tools and methods from the stages of data creation, data storage, data pre-processing, data calculation, data service, data archiving and data destruction. In the data creation stage, specific data access forms are formulated for different sources and data types, and personalized data creation tools are built to receive data completely. In the data storage stage, a unified document metadata storage system is developed by analyzing the characteristics and shortcomings of various types of data, so as to better explain and organize scientific and technological document data. In the data pre-processing stage, various tools are built to realize the formatting pre-processing, parsing, conversion, structuring and other operations of various types of data. In the data computing stage, data enrichment processing, entity relationship extraction and knowledge graph construction are mainly completed. Data provides services through a unified service interface. Data archiving completes data archiving and saving. In the data destruction phase, unnecessary data is safely destroyed. [Results/Conclusions] In this paper, the management and practice based on the life cycle of S&T literature were first carried out based on the core data set Web Of Science BP data , and then explored from the seven phases of creation, storage, pre-processing, calculation, service, archiving and destruction. Finally, based on the DAMA data quality evaluation principle, the comprehensive evaluation and evaluation of the data management effect were carried out from the six dimensions of integrity, uniqueness, real-time, validity, accuracy and consistency. The receiving integrity of data was 100%, and the non-null integrity of data was 59.75%. The uniqueness of data reached 99.23%. The real time of data was controllable. The validity of data met the constraint conditions. The accuracy of the data reached 100%. The consistency of data reached 90%. It basically solved the problem that data can be effectively managed and applied in each life cycle stage. Finally, the management model was verified to take effect and achieve desirable service effect.
Subjects: Library Science，Information Science >> Information Science submitted time 2017-11-08 Cooperative journals: 《数据分析与知识发现》
Abstract：【目的】面向语义出版构建论文写作工具, 在论文写作阶段实现内容结构化、对象化, 使得一篇论文即是一个系统, 论文可运行、可交互、可体验。【方法】采用数字对象和数字模板技术将论文内容(元数据、章节、数据、富媒体等)分解成不同类型数字对象, 数字对象间采用模板进行组织, 通过事件触发机制实现交互, 采用HTML5 网页形式进行编辑和呈现并存储为XML 结构化文档包。【结果】DPaper 结构化论文写作工具已上线, 提供从素材收集(云笔记)、数字对象制作、自动标引参考文献、按期刊版式呈现到Word 文档格式转换等一系列功能, 论文内容实现对象化和部分语义化。【局限】与常规论文编辑器相比, 数字对象编辑器功能还不完善, 还不能创建公式、图形等对象, 排版的灵活性不足。【结论】利用DPaper 写作工具可以在写作阶段由作者构建出满足语义出版应用需求的结构化论文。
Subjects: Library Science，Information Science >> Library Science submitted time 2016-03-10
Abstract：文章对图书馆领域的主流资源发现平台（Elsevier，Springer，中国知网 CNKI）和商业资源发现系统（Primo，Summon，EDS）的页面构造和页面布局等方面进行了多层次多角度的分析，并对多个平台（如Willy，英国国家图书馆，荷兰国家图书馆，美国国会图书馆，美国 NSDL，OCLC，PubMed等）的特色资源和功能进行调研分析，最终借助上述平台的优秀功能，改进我中心自行建设的资源集成发现服务系统，并着重提升用户使用体验。
Peer Review Status:
Awaiting Review
Subjects: Library Science，Information Science >> Library Science submitted time 2016-01-25
Abstract：通过调研国际主要机构的战略规划，归纳出Data Curation 在管理、资源建设、技术基础设施方面存在的主要挑战。针对这些挑战，从战略规划、数据评估与遴选政策、关键技术、审计和认证四方面全面回顾了国际Data Curation 研究、实践的发展情况。分析图书馆在大数据科研环境下可能参与科研数据保管的领域，为图书馆在Data Curation活动中谋求发展机会。
Peer Review Status:Awaiting Review
Subjects: Library Science，Information Science >> Library Science submitted time 2016-01-25
Abstract：目前的图书管理系统，没有把图书检索和图书推荐结合起来，本文介绍的图书管理系统，对图书进行了分类，提供了按书名、作者进行检索，在检索结果页面中，显示推荐结果。本文介绍了该图书管理系统的设计，该网站的推荐系统采用了基于物品的协同过滤算法、基于内容的推荐算法，本文详细介绍了这两个算法，接着，本文全面介绍了该图书管理系统中推荐系统部分的设计。现在，该图书管理系统已经完成了概要设计和详细设计。
Peer Review Status:Awaiting Review
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