Subjects: Library Science，Information Science >> Information Science submitted time 2024-04-18
Abstract： Abstract: Purpose/Significance With the rapid development of social informatization, the spread scope and influence of online public opinions are constantly expanding. The analysis of public opinion intention is helpful for government departments to monitor and manage public opinion and create a healthy network environment. This study aims to sort out the development context and frontier trends in the field of public opinion intention recognition, provide direction for future research on public opinion intention recognition, and promote the development and application of the discipline. Method/Process This study discusses the current research status in the field of public opinion intention recognition, defines the concept and sources of public opinion intention recognition, and summarizes the technical methods, application fields, challenges and development directions of public opinion intention recognition. Result/Conclusion It is found that the current intention recognition of public opinion is mainly applied to the research of opinion leaders, early warning of public emergencies, public opinion governance and education. At the same time, the false information in online public opinion, the ambiguity of network language and the limited big data resources bring challenges to the recognition of public opinion intention. In the future, the process of public opinion intention recognition should focus on false information recognition, implicit information mining, algorithm and resource improvement.
Peer Review Status:
Awaiting Review
Subjects: Library Science，Information Science >> Information Science submitted time 2024-04-17
Abstract： Purpose/Significance Medical device products are the products of clinical scientific research results transformation and knowledge innovation management. As one of the main competition tracks in the science and technology industry, the strength of medical science and technology is an important aspect to measure the country’s overall scientific research ability and environment. Knowledge innovation drives industrial development, product structure reflects the level of knowledge management, and knowledge management involving frontier science and technology is closely related to national strategic planning. From the perspective of product theme mining and evolution sharing, it is of great strategic significance for enterprises and countries to look into the current situation of domain technical knowledge management. Method/Process A comprehensive approach to technical topic identification and analysis is adopted in this study. Through the application of LDA algorithm in the field of machine learning, potential technical topics are identified and clustered from the medical device product data, and then the distribution characteristics and change rules of technical topics in different periods are analyzed. The future technology trend is predicted quantitatively by using hidden Markov model. Using this combination method, the topic distribution, evolution law and future trend of innovative medical devices from 2014 to 2023 are deeply studied. Result/Conclusion 38 technical topics were identified and sorted out using domestic approved innovative medical device product data. The results show the deep development of genetic testing and implanted electrical stimulator technology. Disease diagnosis, surgical navigation and biological mesh are the focus of future technological innovation and product competition. However, from the perspective of quantitative characteristics, China’s research and development strength is relatively weak, and the innovation ability is in a weak position, which needs to attract the attention of enterprise technology research and development institutions and the government.
Peer Review Status:Awaiting Review
Subjects: Library Science，Information Science >> Information Science submitted time 2024-04-14
Abstract： Purpose/Significance In order to address the issues of poor interactivity and low security in traditional electronic medical record big data resources, this paper proposes a blockchain-based electronic medical record big data sharing solution that is decentralized, tamper-proof, and encrypted. Method/Process Firstly, the application of current blockchain technology in the medical field is analyzed. Then, the demands for electronic medical records in the medical market are collected through questionnaire surveys and interviews. Based on this, a five-level blockchain-based electronic medical record big data resource sharing solution is proposed, which incorporates mechanisms such as asymmetric encryption technology, consensus mechanism, and smart contracts. Results/Conclusions This solution reshapes the process of sharing medical big data resources and further improves the application of blockchain in the secure storage and sharing of medical data. It can serve as a reference for relevant companies, hospitals, and researchers.
Peer Review Status:Awaiting Review
Subjects: Library Science，Information Science >> Information Science submitted time 2017-11-08 Cooperative journals: 《数据分析与知识发现》
Abstract：【目的】为更精确地识别网民态度, 监测网络舆情, 提出一种基于SVM 多特征融合的情感5 级分类方法。【方法】从词性特征、情感特征、句式特征、语义特征4 个方面, 提取动词、名词、情感词、否定词等14 个特征, 运用SVM 方法对微博情感进行5 级分类。【结果】实验结果表明, 该方法对情感5 级分类的准确率为82.40%,召回率为81.91%, F 值为82.10%。【局限】训练语料的规模有待进一步提高。【结论】该方法在情感5 级分类方面取得较好的效果。
Subjects: Library Science，Information Science >> Information Science submitted time 2017-11-08 Cooperative journals: 《数据分析与知识发现》
Abstract：【目的】为更精确地识别网民态度, 监测网络舆情, 提出一种基于SVM 多特征融合的情感5 级分类方法。【方法】从词性特征、情感特征、句式特征、语义特征4 个方面, 提取动词、名词、情感词、否定词等14 个特征, 运用SVM 方法对微博情感进行5 级分类。【结果】实验结果表明, 该方法对情感5 级分类的准确率为82.40%,召回率为81.91%, F 值为82.10%。【局限】训练语料的规模有待进一步提高。【结论】该方法在情感5 级分类方面取得较好的效果。
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