Subjects: Library Science，Information Science >> Library Science submitted time 2023-10-08 Cooperative journals: 《知识管理论坛》
Abstract： [Purpose/significance] This paper focuses on the development of the open science movement and the influence of scientific data on scientific research, introduces some cases of the integration of scientific literature and scientific data, and states the methods and problems of integration. [Method/process] The author described the status of separation of scientific literature and scientific data, explained the background that promotes the integration of these two things. Then, by the case study, it introduced three types performance of the integration of scientific literature and scientific data. [Result/conclusion] The integration of scientific literature and scientific data is needed by scientific research, as well as a form of influence on modern scientific research in the era of open science and big data. In practical application, there are mainly three ways: “hard connection”, “soft connection” and “deep integration”. The integration of literature and data need to be promoted by the comprehensive measures from the main institutions of all fields.
Subjects: Library Science，Information Science >> Library Science submitted time 2023-07-26 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] This paper aims at summarizing the transition and development of digital resources construction, especially the second one triggered by open resources, and probing the future development direction of digital resources construction in the research libraries. [Method/process] This paper takes the Libraries of Chinese Academy of Sciences as an example to scrutinize the practice and effectiveness of the digital resources construction, and to anticipate the future development based on the construction of comprehensive science and technology resources and open resources, as well as the connection and presentation of knowledge elements. [Result/conclusion] Research libraries are faced with many problems in the transition of digital resources construction. The following suggestions are proposed in this paper:①developing the detailed digital resources construction schemas; ②allocating funds, manpower and technology rationally; ③clarifying use right of open resources and promoting open access movement; ④strengthening inter-library cooperation and sharing of open resources construction; ⑤strengthening cross-border cooperation in knowledge resources organization.
Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] The identification and analysis of policy tools is one of the important methods of policy research. However, the identification of policy tools is mostly manual. In this article, we attempt to use deep learning methods to automatically identify policy tools, aiming at improving the efficiency of policy tool identification. [Method/process] We designed and implemented the policy tool automatic identification experimental process of "Policy data collection and cleaning-policy tool manual indexing-model training-result interpretation". We take the open government data policies of Beijing, Shanghai, Guangzhou, and Guiyang as an example to compare the performance of traditional machine learning methods and deep learning methods on the task of identifying policy tools. In addition, we have proposed to integrate policy global information to identify policy tools in each paragraph, and our experiments have proved the effectiveness of the idea. [Result/conclusion] The deep learning model CNN achieves an accuracy of 76.51% on the full test data, and the CNN model that integrates global information achieves an accuracy of 77.13%. When evaluating the high-confident results of the model, we find that the model achieves an accuracy of 95.44% on 55.63% of the test data, which has reached the practical requirements. This shows that more than half of the data can be indexed with the model’s high-confidence results without manual review. Deep learning methods have been applied to the automatic identification of policy tools and has achieved good results. It could help to improve the efficiency of policy tool labeling and provide positive experience for the automatic identification of policy tools with big data. And it provides a positive experience for automatic identification of policy tools with large data volumes.
Subjects: Library Science，Information Science >> Information Science submitted time 2017-12-05 Cooperative journals: 《数据分析与知识发现》
Abstract：【目的】分析文本相似度计算方法, 了解该领域的发展态势。【文献范围】在 CNKI 和 Web of Science 中 分别以检索式“篇名: 文本相似度 OR 篇名: 词汇相似度 OR 篇名: 语义相似度”和“TI: ‘text similarity’ or ‘semantic similarity’ or ‘lexical similarity’ ”并限定文献类型进行检索, 最终得到 69 篇重点文献。【方法】对文本相 似度计算方法进行系统梳理, 分析重点方法的基本思想、特点并总结未来发展方向。【结果】形成了较为全面的 分类描述体系, 文本相似度计算方法可分为 4 类: 基于字符串的方法、基于语料库的方法、基于世界知识的方法 和其他方法。其中, 基于神经网络和基于世界知识的方法以及针对跨领域文本的相似度计算将成为该领域的发 展趋势。【局限】仅将不同方法本身作为探讨的核心, 未进一步分析方法的应用情况。【结论】有助于全面把握 和深入了解文本相似度计算方法的研究现状和未来趋势。
Subjects: Library Science，Information Science >> Information Science submitted time 2017-11-30 Cooperative journals: 《数据分析与知识发现》
Abstract：【目的】分析文本相似度计算方法, 了解该领域的发展态势。【文献范围】在 CNKI 和 Web of Science 中 分别以检索式“篇名: 文本相似度 OR 篇名: 词汇相似度 OR 篇名: 语义相似度”和“TI: ‘text similarity’ or ‘semantic similarity’ or ‘lexical similarity’ ”并限定文献类型进行检索, 最终得到 69 篇重点文献。【方法】对文本相 似度计算方法进行系统梳理, 分析重点方法的基本思想、特点并总结未来发展方向。【结果】形成了较为全面的 分类描述体系, 文本相似度计算方法可分为 4 类: 基于字符串的方法、基于语料库的方法、基于世界知识的方法 和其他方法。其中, 基于神经网络和基于世界知识的方法以及针对跨领域文本的相似度计算将成为该领域的发 展趋势。【局限】仅将不同方法本身作为探讨的核心, 未进一步分析方法的应用情况。【结论】有助于全面把握 和深入了解文本相似度计算方法的研究现状和未来趋势。
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