Accurate Portraits of Scientific Resources and Knowledge Service Components
Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia(智能电信软件与多媒体北京重点实验室);School of Computer Science (National Pilot School of Software Engineering)(计算机学院);Beijing University of Posts and Telecommunications(北京邮电大学)
With the advent of the cloud computing era, the cost of creating, capturing, and managing information has gradually decreased. The amount of data on the Internet is showing explosive growth, and more scientific and technological resources are being uploaded to the network. Different from news and social media data, scientific and technological resources are mainly composed of academic-style resources or entities, such as papers, patents, authors, and research institutions. There is a rich relationship network between these resources, from which a large amount of cutting-edge scientific and technological information can be mined. Existing scientific resource management and classification standards are difficult to completely cover all entities and associations, and they cannot accurately extract the important information contained in scientific and technological resources. Therefore, how to construct a complete and accurate representation of scientific and technological resources from structured and unstructured reports and texts, and how to tap the potential value of scientific and technological resources, are urgent problems. A feasible solution is to construct accurate portraits of scientific and technological resources by combining knowledge graph technology, text representation learning, entity extraction, and knowledge service components.
Knowledge Graph and Accurate Portrait Construction of Scientific and Technological Academic Conferences
Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia, School of Computer Science (National Pilot School of Software Engineering), Beijing University of Posts and Telecommunications(北京智能电信软件与多媒体重点实验室,计算机学院(国家软件工程试点学院),北京邮电大学)
Retrieval of Scientific and Technological Resources for Experts and Scholars
School of Computer Science (National Pilot School of Software Engineering), Beijing University of Posts and Telecommunications(北京邮电大学计算机学院(国家软件工程试点学院));Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia(北京智能电信软件与多媒体重点实验室)
Research on Intellectual Property Resource Profile and Evolution Law
Beijing Key Laboratory of Intelligent Communication Software and Multimedia(智能通信软件与多媒体北京重点实验室);School of Computer, Beijing University of Posts and Telecommunications(北京邮电大学计算机学院);Beijing University of Posts and Telecommunications(北京邮电大学)
Connecting web-based mapping services with scientific data repositories: collaborative curation and retrieval of simulation data via a geospatial interface
Trends in scientific research in Online Information Review. Part 1. Production, impact and research collaboration
该研究基于Web of Science,分析了2000年至2014年发表的758篇文章。我们的分析包括出版物的产出,作者,机构和国家的生产模式,引用和合作。进行了一项社会网络分析,以确定研究人员和机构的主要群体以及各国之间的合作。该研究显示,1097名作者和453个机构为该杂志做出了贡献。合作指数逐步上升,研究期间的平均合作程度为1.98。大多数论文是由大学附属专业人员撰写的。高被引论文涉及在线和数字环境、电子学习系统、移动服务、Web 2.0和引文分析。这项工作是在图书馆学和情报学的领先期刊,在线信息评论的文献计量学分析。