National Science Library,Chinese Academy of Sciences
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印度生物技术的创新经验
No full textThis rapid literature review has found that evidence on India’s experience and achievements in biotechnology is largely generated by government reports and state agency websites. A review of academic studies, government publications and Government of Indian websites, as well as reports issued by different development agencies was conducted to gather evidence on achievements in the Indian experience of innovation in biotechnology. Much of the evidence gathered is based on Government of India reports. The report particularly focuses on the evidence from India’s innovation experience on the health, agriculture, clean energy and waste to value sectors. The literature on these sectors mainly focuses on what has been achieved with sector specific evidence on how innovation was supported in specific programmes and projects. Some of the key examples gathered address varying levels of innovation development. These include national level sectoral strategies, policy development, incubation, international collaborations and support for commercialization of ideas.
K4D helpdesk reports provide summaries of current research, evidence and lessons learned. This report was commissioned by the UK Department for International Development.</p
中国图书情报档案领域智能技术研究演化分析——基于CiteSpace
No full text为了解我国图书情报档案领域智能技术研究的发展历程，发现当前研究热点和未来发展趋势，该文通过中国知网（CNKI）检索相关文献，借助SATI、Excel、iteSpace等工具进行数据挖掘，绘制知识图谱，对该领域的发展历程、研究热点、研究人员和研究机构进行可视化分析，以揭示该领域发展的三个阶段，展现各学科研究热点的演化脉络、研究人员和研究机构的关系网络，并指出该领域的发展方向。</p
基于语义TRIZ的专利技术挖掘
No full text专利技术创新是技术创新的核心，它对提升创新主体的创新能力，构建企业核心竞争力，促进现代产业发展，制定科技前沿发展战略以及深化科技领域改革等方面都具有重要意义。专利技术挖掘是支撑专利技术创新的重要抓手和尖兵利器，贯穿技术创新的始终。语义TRIZ可以有效揭示专利特有的“技术问题、技术方案、技术功能与技术效果”等信息，被广泛运用于专利技术挖掘之中。随着以人工智能和知识图谱为代表的信息技术快速发展，专利技术挖掘，特别是基于语义TRIZ的分析越来越成为进行深度专利情报服务的关键手段和核心方法。
全书共7章，遵循提出问题、分析问题、解决问题与应用实践的研究思路，针对基于语义TRIZ的专利技术挖掘的理论体系、方法技术和应用进行系统介绍。最后，介绍了作者研发的基于语义TRIZ的专利技术挖掘系统。
《基于语义TRIZ的专利技术挖掘》一书的研究成果不仅有力地支撑了国家社会科学基金项目、科技部创新方法工作专项项目、中国科学院知识产权信息服务专项、中国科学院科技服务网络计划择优支持项目等重大科研任务，对技术挖掘研究与应用的进一步发展起积极的推动作用，还将进一步凸显技术挖掘作为一门“数据+AI”驱动的科技情报分析范式下的应用性学科的重要作用。本书适合科技情报学、信息科学、数据科学、管理科学与工程等相关专业高校师生、科研工作者及相关管理人员阅读和参考。</p
Output regularities of China’s international collaboration research projects funded by NSFC
No full textProfiling and predicting the problem-solving patterns in China’s research systems: A methodology of intelligent bibliometrics and empirical insights
No full textUncovering the driving forces, strategic landscapes, and evolutionary mechanisms of China’s research systems is attracting rising interest around the globe. One such interest is to understand the problem-solving patterns in China’s research systems now and in the future. Targeting a set of high-quality research articles published by Chinese researchers between 2009 and 2018, and indexed in the Essential Science Indicators database, we developed an intelligent bibliometrics-based methodology for identifying the problem-solving patterns from scientific documents. Specifically, science overlay maps incorporating link prediction were used to profile China’s disciplinary interactions and predict potential cross-disciplinary innovation at a macro level. We proposed a function incorporating word embedding techniques to represent subjects, actions, and objects (SAO) retrieved from combined titles and abstracts into vectors and constructed a tri-layer SAO network to visualize SAOs and their semantic relationships. Then, at a micro level, we developed network analytics for identifying problems and solutions from the SAO network, and recommending potential solutions for existing problems. Empirical insights derived from this study provide clues to understand China’s research strengths and the science policies beneath them, along with the key research problems and solutions Chinese researchers are focusing on now and might pursue in the future.</p