| 面向智慧知识服务的科技文献大数据体系建设 |
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| 引用本文： | 吴振新,钱力,谢靖,常志军,许丽媛,赵艳.面向智慧知识服务的科技文献大数据体系建设[J].图书情报工作,2020,64(24):63-72. |
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| 作者姓名： | 吴振新 钱力 谢靖 常志军 许丽媛 赵艳 |
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| 作者单位： | 1. 中国科学院文献情报中心 北京 100190;
2. 中国科学院大学经济与管理学院图书情报与档案管理系 北京 100190 |
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| 基金项目： | 本文受"中国科学院文献情报中心成立七十周年主题论坛与纪念文集出版"项目资助出版。 |
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| 摘 要： | 目的/意义] 探索构建文献情报大数据知识资源体系,支撑面向多领域的智慧知识服务。方法/过程] 基于AI应用需求,借鉴业界经验,梳理现有资源体系的问题,从多层次多维度扩展资源体系;构建可靠数据处理流程和计算平台,支持高效数据采集和处理;研发智能化数据治理工具,实现知识资源的有效治理,确保提供高质量数据资源。结果/结论] 已初步形成覆盖多类型、多学科的科技文献大数据知识资源体系,构建完成高度自动化的数据采集治理流程,实施多重数据质量控制,积累数亿高质量数据,且为多个知识服务提供数据支撑。
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| 关 键 词： | 科技大数据 知识资源体系 数据汇聚 智慧知识服务 |
| 收稿时间： | 2020-11-05 |
| 修稿时间： | 2020-12-20 |
Construction of Sci-Tech Big Data System oriented to Intelligent Knowledge Service |
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| Wu Zhenxin,Qian Li,Xie Jing,Chang Zhijun,Xu Liyuan,Zhao Yan.Construction of Sci-Tech Big Data System oriented to Intelligent Knowledge Service[J].Library and Information Service,2020,64(24):63-72. |
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| Authors: | Wu Zhenxin Qian Li Xie Jing Chang Zhijun Xu Liyuan Zhao Yan |
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| Institution: | 1. National Science Library, Chinese Academy Sciences, Beijing 100190;
2. Department of Library, Information and Archives Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190 |
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| 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. |
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| Keywords: | science and technological big data knowledge resource architecture data aggregation intelligent knowledge services |
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