The journal Chemical Research in Chinese Universities is a comprehensive academic journal in the field of chemistry,published bimonthly since 1984.The journal publishes research articles,letters/communications and rev...The journal Chemical Research in Chinese Universities is a comprehensive academic journal in the field of chemistry,published bimonthly since 1984.The journal publishes research articles,letters/communications and reviews written by faculty members,researchers and postgraduates in universities,colleges and research institutes all over China and overseas.It reports the latest and the most creative results of important fundamental research in all aspects of chemistry and of developments with significant consequences across sub-disciplines.This journal is sponsored by Jilin University and mandated by the Ministry of Education of P.R.China.展开更多
The journal Chemical Research in Chinese Universities is a comprehensive academic journal in the field of chemistry,published bimonthly since 1984.The journal publishes research articles,letters/communications and rev...The journal Chemical Research in Chinese Universities is a comprehensive academic journal in the field of chemistry,published bimonthly since 1984.The journal publishes research articles,letters/communications and reviews written by faculty members,researchers and postgraduates in universities,colleges and research institutes all over China and overseas.It reports the latest and the most creative results of important fundamental research in all aspects of chemistry and of developments with significant consequences across sub-disciplines.This journal is sponsored by Jilin University and mandated by the Ministry of Education of P.R.China.展开更多
Tracking and analyzing data from research projects is critical for understanding research trends and supporting the development of science and technology strategies.However,the data from these projects is often comple...Tracking and analyzing data from research projects is critical for understanding research trends and supporting the development of science and technology strategies.However,the data from these projects is often complex and inadequate,making it challenging for researchers to conduct in-depth data mining to improve policies or management.To address this problem,this paper adopts a top-down approach to construct a knowledge graph(KG)for research projects.Firstly,we construct an integrated ontology by referring to the metamodel of various architectures,which is called the meta-model integration conceptual reference model.Subsequently,we use the dependency parsing method to extract knowledge from unstructured textual data and use the entity alignment method based on weakly supervised learning to classify the extracted entities,completing the construction of the KG for the research projects.In addition,a knowledge inference model based on representation learning is employed to achieve knowledge completion and improve the KG.Finally,experiments are conducted on the KG for research projects and the results demonstrate the effectiveness of the proposed method in enriching incomplete data within the KG.展开更多
The limitations of traditional approaches to selection problems are examined. A problemsolving strategy is presented in which decision-support and knowledge-based techniques play complementary roles. An approach to th...The limitations of traditional approaches to selection problems are examined. A problemsolving strategy is presented in which decision-support and knowledge-based techniques play complementary roles. An approach to the representation of knowledge to support the problem-solving strategy is presented which avoids commitment to a specific programming language or implementation environment. The problem of choosing a home is used to illustrate the representation of knowledge in a specific problem domain. Techniques for implementation of the problem-solving strategy are described. Knowledge elicitation techniques and their implementation in a development shell for application of the problem-solving strategy to any selection problem are also described.展开更多
立足科技情报知识服务视角,梳理AI for Science (AI4S)推动的“平台科研”范式内涵与框架。根据库恩范式理论论述了AI4S推动科研范式革新的必然性,采用培根归纳法总结的科学研究流程作为框架线索,阐明创新知识服务与“平台科研”范式的...立足科技情报知识服务视角,梳理AI for Science (AI4S)推动的“平台科研”范式内涵与框架。根据库恩范式理论论述了AI4S推动科研范式革新的必然性,采用培根归纳法总结的科学研究流程作为框架线索,阐明创新知识服务与“平台科研”范式的互促共进关系并作为理论指导。创新知识服务视角下的“平台科研”范式以服务科研创新活动为宗旨,主要内容包括知识表示视角下的科学数据管理、知识融合视角下的通用知识库构建、知识推理视角下的科学假设预测、知识发现视角下的科学实验执行和知识应用视角下的工业赋能。本文提出了一种创新知识服务视角下的“平台科研”范式框架,旨在从创新知识服务角度理解“平台科研”范式,厘清各主要环节创新知识服务的核心研究内容,以期成为科技情报研究领域的新兴知识生长点,为我国抢抓AI4S科研范式革新机遇提供参考思路。展开更多
认知语篇研究是认知与语篇研究的前沿交叉领域。本文基于Web of Science核心数据库和CNKI数据库,追踪2000—2022年间国内外认知语篇研究的热点,分析其研究趋势并进行展望。分析表明,认知语篇研究主要涉及语篇参与者在语篇建构和理解中...认知语篇研究是认知与语篇研究的前沿交叉领域。本文基于Web of Science核心数据库和CNKI数据库,追踪2000—2022年间国内外认知语篇研究的热点,分析其研究趋势并进行展望。分析表明,认知语篇研究主要涉及语篇参与者在语篇建构和理解中的心理过程和认知注意,呈现出认知过程导向性和行业实践应用性特征;跨学科融合趋势日渐凸显,内涵和外延不断丰富;研究方法多样,理论基础多源。基于此,未来认知语篇研究需趋向于完善理论建构和多重数据实证研究,持续拓展研究领域,同时深化本土研究,以推动该领域发展。展开更多
文摘The journal Chemical Research in Chinese Universities is a comprehensive academic journal in the field of chemistry,published bimonthly since 1984.The journal publishes research articles,letters/communications and reviews written by faculty members,researchers and postgraduates in universities,colleges and research institutes all over China and overseas.It reports the latest and the most creative results of important fundamental research in all aspects of chemistry and of developments with significant consequences across sub-disciplines.This journal is sponsored by Jilin University and mandated by the Ministry of Education of P.R.China.
文摘The journal Chemical Research in Chinese Universities is a comprehensive academic journal in the field of chemistry,published bimonthly since 1984.The journal publishes research articles,letters/communications and reviews written by faculty members,researchers and postgraduates in universities,colleges and research institutes all over China and overseas.It reports the latest and the most creative results of important fundamental research in all aspects of chemistry and of developments with significant consequences across sub-disciplines.This journal is sponsored by Jilin University and mandated by the Ministry of Education of P.R.China.
基金supported by the National Natural Science Foundation of China(72101263).
文摘Tracking and analyzing data from research projects is critical for understanding research trends and supporting the development of science and technology strategies.However,the data from these projects is often complex and inadequate,making it challenging for researchers to conduct in-depth data mining to improve policies or management.To address this problem,this paper adopts a top-down approach to construct a knowledge graph(KG)for research projects.Firstly,we construct an integrated ontology by referring to the metamodel of various architectures,which is called the meta-model integration conceptual reference model.Subsequently,we use the dependency parsing method to extract knowledge from unstructured textual data and use the entity alignment method based on weakly supervised learning to classify the extracted entities,completing the construction of the KG for the research projects.In addition,a knowledge inference model based on representation learning is employed to achieve knowledge completion and improve the KG.Finally,experiments are conducted on the KG for research projects and the results demonstrate the effectiveness of the proposed method in enriching incomplete data within the KG.
文摘The limitations of traditional approaches to selection problems are examined. A problemsolving strategy is presented in which decision-support and knowledge-based techniques play complementary roles. An approach to the representation of knowledge to support the problem-solving strategy is presented which avoids commitment to a specific programming language or implementation environment. The problem of choosing a home is used to illustrate the representation of knowledge in a specific problem domain. Techniques for implementation of the problem-solving strategy are described. Knowledge elicitation techniques and their implementation in a development shell for application of the problem-solving strategy to any selection problem are also described.
文摘立足科技情报知识服务视角,梳理AI for Science (AI4S)推动的“平台科研”范式内涵与框架。根据库恩范式理论论述了AI4S推动科研范式革新的必然性,采用培根归纳法总结的科学研究流程作为框架线索,阐明创新知识服务与“平台科研”范式的互促共进关系并作为理论指导。创新知识服务视角下的“平台科研”范式以服务科研创新活动为宗旨,主要内容包括知识表示视角下的科学数据管理、知识融合视角下的通用知识库构建、知识推理视角下的科学假设预测、知识发现视角下的科学实验执行和知识应用视角下的工业赋能。本文提出了一种创新知识服务视角下的“平台科研”范式框架,旨在从创新知识服务角度理解“平台科研”范式,厘清各主要环节创新知识服务的核心研究内容,以期成为科技情报研究领域的新兴知识生长点,为我国抢抓AI4S科研范式革新机遇提供参考思路。
文摘认知语篇研究是认知与语篇研究的前沿交叉领域。本文基于Web of Science核心数据库和CNKI数据库,追踪2000—2022年间国内外认知语篇研究的热点,分析其研究趋势并进行展望。分析表明,认知语篇研究主要涉及语篇参与者在语篇建构和理解中的心理过程和认知注意,呈现出认知过程导向性和行业实践应用性特征;跨学科融合趋势日渐凸显,内涵和外延不断丰富;研究方法多样,理论基础多源。基于此,未来认知语篇研究需趋向于完善理论建构和多重数据实证研究,持续拓展研究领域,同时深化本土研究,以推动该领域发展。