In the big data environment, the construction of massive S&T literature data resources needs intelligent technical assistance. With a focus on comparing the domestic and foreign knowledge organization systems and ...In the big data environment, the construction of massive S&T literature data resources needs intelligent technical assistance. With a focus on comparing the domestic and foreign knowledge organization systems and their applications, this article analyzes and summarizes the gaps in related researches and applications at home and abroad. A knowledge organization system framework for S&T literature data resources is presented in the article. Starting from the basic element of knowledge organization system, it also proposes and designs terminology-based analysis methods and technologies for S&T literature. Based on this framework, it proposes ideas and develops corresponding software tool to carry out relevant experiments. It gives an overview of theories and technologies method for future research.展开更多
Purpose: The aim of this study is to develop and implement a quality-control system to ensure authority control of the different knowledge units for the Scientific & Technological Knowledge Organization Systems(ST...Purpose: The aim of this study is to develop and implement a quality-control system to ensure authority control of the different knowledge units for the Scientific & Technological Knowledge Organization Systems(STKOS).Design/methodology/approach: First, we analyzed quality-control requirements based on the construction of the STKOS Metathesaurus. Then we designed a quality-control framework, the task management and transfer mechanism, and a service model. Afterwards, we carried out the experiments to check the rules and algorithms used in the system. Finally, the system was developed, and gradually optimized during its service.Findings: The quality-control system supports collaborative knowledge construction, as well as consistency checks of knowledge units with different granularity levels, including terminologies, relationships, and concepts. The system can be flexibly configured.Research limitations: The system is oriented to an English-language knowledge organization system, and may not perform well with Chinese-language systems and ontologies.Practical implications: The system can be used to support the construction of a single knowledge organization system, as well as data warehousing and interoperable knowledge organization systems. Originality/value: The STKOS quality-control system not only focuses on content building for the knowledge system, but also supports collaborative task management.展开更多
基金Supported by the National Social Science Fund of China(No.18BTQ054)
文摘In the big data environment, the construction of massive S&T literature data resources needs intelligent technical assistance. With a focus on comparing the domestic and foreign knowledge organization systems and their applications, this article analyzes and summarizes the gaps in related researches and applications at home and abroad. A knowledge organization system framework for S&T literature data resources is presented in the article. Starting from the basic element of knowledge organization system, it also proposes and designs terminology-based analysis methods and technologies for S&T literature. Based on this framework, it proposes ideas and develops corresponding software tool to carry out relevant experiments. It gives an overview of theories and technologies method for future research.
基金supported by the Ministry of Science and Technology of China(Grant No.:2011BAH10B02)
文摘Purpose: The aim of this study is to develop and implement a quality-control system to ensure authority control of the different knowledge units for the Scientific & Technological Knowledge Organization Systems(STKOS).Design/methodology/approach: First, we analyzed quality-control requirements based on the construction of the STKOS Metathesaurus. Then we designed a quality-control framework, the task management and transfer mechanism, and a service model. Afterwards, we carried out the experiments to check the rules and algorithms used in the system. Finally, the system was developed, and gradually optimized during its service.Findings: The quality-control system supports collaborative knowledge construction, as well as consistency checks of knowledge units with different granularity levels, including terminologies, relationships, and concepts. The system can be flexibly configured.Research limitations: The system is oriented to an English-language knowledge organization system, and may not perform well with Chinese-language systems and ontologies.Practical implications: The system can be used to support the construction of a single knowledge organization system, as well as data warehousing and interoperable knowledge organization systems. Originality/value: The STKOS quality-control system not only focuses on content building for the knowledge system, but also supports collaborative task management.