Subjects: Management Science >> Science ology and Management submitted time 2023-05-15
Abstract： Objective Reform of scientific research evaluation has made phased progress, but issues still exist, such as the lack of innovative evaluation methods and an incomplete evaluation system. Methods To address these issues, this study, based on existing scientific research evaluation and incentive systems, designs a diversified evaluation system for the research process using the ICDP method, and establishes a corresponding platform for diversified evaluation of the research process. Results Taking a key laboratory of the Chinese Academy of Sciences as a case, this paper elaborates on the index system architecture of the chemical engineering discipline and demonstrates the calculation process of overall evaluation and participant evaluation. Limitations The evaluation system described in this study takes into account the characteristics of the subject being assessed and adopts a combination of subjective and objective evaluations. It may be applicable to disciplines similar to this one. Other disciplines can refer to the principles of evaluation system design and design an evaluation system that suits the characteristics of their discipline. Conclusions A diversified evaluation and incentive system for the research process, characterized by information storage and recording at key nodes, can effectively solve prominent issues in the reform of scientific research, and is conducive to the sustainable development of the scientific research process ecosystem.
Peer Review Status:
Awaiting Review
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 results of the LDA model is sometimes unsatisfactory due to some meaningless topics mixed together. Therefore, it's quite necessary to establish an effective topic filtering method to eliminate these noise topics and to ensure the accuracy of subsequent evolution analysis.[Method/process] Based on the co-occurrence relationship between keywords, keywords relevance index (KRI) was constructed. Taking the field of single cell research as an example, KRI values of the distribution of theme-keywords were calculated and compared with the results of manual interpretation.[Result/conclusion] Experimental results show that this method can effectively eliminate meaningless noise topics in the LDA model recognition results, which can improve the accuracy of topic recognition and the subsequent topic evolution analysis. It also helps to reduce the dependence on manual interpretation in the process of topic identification through the topic model method.
Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] Artificial Intelligence is triggering a chain reaction-like scientific breakthrough, leading a new round of scientific and technological revolution and industrial transformation, how to use AI to provide Intelligent Knowledge Services and Intelligent Information system is the current focus of attention and hot spot. [Method/process] This paper analyzed AI technology and big data from inside and outside the library and information domain to bring new platforms, new services and new opportunities and challenges to the knowledge service paradigm, and provided the idea of building the Intelligent Knowledge Service ecosystem driven by "AI technology and big data", and built the "science brain" method from the three levels of intelligent data, wisdom center and intelligence service, and provided an open intelligent knowledge service ecological environment covering science and technology management, scientific and technological innovation and social academic information environment. [Result/conclusion] As an exploration building of National Science Library Chinese Academy of Sciences, about Data Lake of Library and Information, Intelligent Knowledge Service engine, Intelligent Knowledge Discovery, Intelligent Knowledge Management, Intelligent Knowledge Analysis and Intelligent Sense Environment, and good results have been achieved. In the future, AI technology for big data government, fine-grained knowledge recognition, precision service and so on, still need to be further improved in data, technology and service models.
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