Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] Combing the interdisciplinary research, summarizing the existing research problems, providing references for evaluating the effect of interdisciplinary research and promoting the development of interdisciplinary research. [Method/process] This paper first analyzed the related concepts of interdisciplinary research, and then, on the basis of the research at home and abroad, from the perspectives of interdisciplinary theoretical research(interdisciplinary research in talent development and education, types of interdisciplinary research, internal and external motivation and obstacles of interdisciplinary research), interdisciplinary measurement research(interdisciplinary measurement methods, interdisciplinary measurement indicators), interdisciplinary law research (interdisciplinary research impact two-way measurement, interdisciplinary research topic identification) to summarize it. At the end of the paper, pointing out the existing research deficiencies and putting forward the prospect for the future development. In this research, we can provide help for the follow-up research from the perspective of the combination of micro-deep analysis and macro-overall construction. [Result/conclusion] At present, there are some deficiencies in interdisciplinary research:the faculty and curriculum system need to be further optimized; the diversity of research objects needs to be improved; the interdisciplinary measurement methods and measurement indicators need to be systematized; the subject classification system needs to be further defined; the two-way influencing factors of interdisciplinary are not comprehensive; the subject identification methods are not complete; the qualitative and quantitative methods need to be combined with each other. Future research can be conducted in-depth analysis of the above deficiencies.
Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] Through related research and practice,ideas and references are provided for the use of WeChat Mini Programs to promote subject knowledge service. [Method/process] This paper analyzed the characteristics and service status of WeChat Mini Programs, proposed the mobile knowledge service framework and model of " big environment, deep discovery, small front end and rich ecology" centered with users based on WeChat Mini programs. It studied the service contents of WeChat Mini Programs for the perspective of information service, knowledge service and personalized service. This paper took the WeChat Mini Programs of "Stem Cell Helper" as an example for case study, and it is proved the feasibility of the method. [Result/conclusion] It believes that, the Mini Programs ecology can also carry a wealth of subject knowledge service applications and support the user's scientific and innovative activities from the mobile terminal with proper planning and scientific layout.
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 and analysis of policy tools is one of the important methods of policy research. However, the identification of policy tools is mostly manual. In this article, we attempt to use deep learning methods to automatically identify policy tools, aiming at improving the efficiency of policy tool identification. [Method/process] We designed and implemented the policy tool automatic identification experimental process of "Policy data collection and cleaning-policy tool manual indexing-model training-result interpretation". We take the open government data policies of Beijing, Shanghai, Guangzhou, and Guiyang as an example to compare the performance of traditional machine learning methods and deep learning methods on the task of identifying policy tools. In addition, we have proposed to integrate policy global information to identify policy tools in each paragraph, and our experiments have proved the effectiveness of the idea. [Result/conclusion] The deep learning model CNN achieves an accuracy of 76.51% on the full test data, and the CNN model that integrates global information achieves an accuracy of 77.13%. When evaluating the high-confident results of the model, we find that the model achieves an accuracy of 95.44% on 55.63% of the test data, which has reached the practical requirements. This shows that more than half of the data can be indexed with the model’s high-confidence results without manual review. Deep learning methods have been applied to the automatic identification of policy tools and has achieved good results. It could help to improve the efficiency of policy tool labeling and provide positive experience for the automatic identification of policy tools with big data. And it provides a positive experience for automatic identification of policy tools with large data volumes.
Hits
Hits
Downloads
Comment