With the popularization of social media,public opi-nion information on emergencies spreads rapidly on the Internet,the impact of negative public opinions on an event has become more significant.Based on the organizati...With the popularization of social media,public opi-nion information on emergencies spreads rapidly on the Internet,the impact of negative public opinions on an event has become more significant.Based on the organizational form of public opinion information,the knowledge graph is used to construct the knowledge base of public opinion risk cases on the emer-gency network.The emotion recognition model of negative pub-lic opinion information based on the bi-directional long short-term memory(BiLSTM)network is studied in the model layer design,and a linear discriminant analysis(LDA)topic extraction method combined with association rules is proposed to extract and mine the semantics of negative public opinion topics to real-ize further in-depth analysis of information topics.Focusing on public health emergencies,knowledge acquisition and knowl-edge processing of public opinion information are conducted,and the experimental results show that the knowledge graph framework based on the construction can facilitate in-depth theme evolution analysis of public opinion events,thus demon-strating important research significance for reducing online pub-lic opinion risks.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
Recently, high-precision trajectory prediction of ballistic missiles in the boost phase has become a research hotspot. This paper proposes a trajectory prediction algorithm driven by data and knowledge(DKTP) to solve ...Recently, high-precision trajectory prediction of ballistic missiles in the boost phase has become a research hotspot. This paper proposes a trajectory prediction algorithm driven by data and knowledge(DKTP) to solve this problem. Firstly, the complex dynamics characteristics of ballistic missile in the boost phase are analyzed in detail. Secondly, combining the missile dynamics model with the target gravity turning model, a knowledge-driven target three-dimensional turning(T3) model is derived. Then, the BP neural network is used to train the boost phase trajectory database in typical scenarios to obtain a datadriven state parameter mapping(SPM) model. On this basis, an online trajectory prediction framework driven by data and knowledge is established. Based on the SPM model, the three-dimensional turning coefficients of the target are predicted by using the current state of the target, and the state of the target at the next moment is obtained by combining the T3 model. Finally, simulation verification is carried out under various conditions. The simulation results show that the DKTP algorithm combines the advantages of data-driven and knowledge-driven, improves the interpretability of the algorithm, reduces the uncertainty, which can achieve high-precision trajectory prediction of ballistic missile in the boost phase.展开更多
结合国内图书馆普遍开展的论文引证检索服务的实际需求,在大量工作实践的基础上,设计并实现了一款基于ISI Web of Knowledge平台检索结果引证检索统计报告的软件,能够根据不同的统计指标,对检索结果进行快速统计。实践证明,该软件提高...结合国内图书馆普遍开展的论文引证检索服务的实际需求,在大量工作实践的基础上,设计并实现了一款基于ISI Web of Knowledge平台检索结果引证检索统计报告的软件,能够根据不同的统计指标,对检索结果进行快速统计。实践证明,该软件提高了工作效率的同时,保证了正确率。展开更多
基于ISI Web of Knowledge平台,对8所纺织背景高校在2001—2011年间的科技论文进行了多角度的统计和分析,探讨了8所纺织背景高校近年来的学科发展现状和趋势,客观评价其学科研究特点和学术影响力,为纺织背景高校增强自身自然科学基础研...基于ISI Web of Knowledge平台,对8所纺织背景高校在2001—2011年间的科技论文进行了多角度的统计和分析,探讨了8所纺织背景高校近年来的学科发展现状和趋势,客观评价其学科研究特点和学术影响力,为纺织背景高校增强自身自然科学基础研究提供参考和帮助,并为其进一步发展提供可参考的定量依据.展开更多
随着学校对图书馆经费投入的不断增加,数字环境下图书馆的合理使用变得越来越重要,其表现在数字资源上要有较多的用户访问和下载.从成员馆对比、登录情况、检索情况和成本等角度统计分析了东华大学ISI Web of Knowledge数据库使用情况,...随着学校对图书馆经费投入的不断增加,数字环境下图书馆的合理使用变得越来越重要,其表现在数字资源上要有较多的用户访问和下载.从成员馆对比、登录情况、检索情况和成本等角度统计分析了东华大学ISI Web of Knowledge数据库使用情况,并分析讨论了读者群和多校区使用情况等,为图书馆电子资源订购提供有效依据.展开更多
The conceptions of the knowledge screen generated by S-rough sets are given: f- screen and - screen , and then puts forward - filter theorem, - filter theorem of knowledge. At last, the applications of knowledge separ...The conceptions of the knowledge screen generated by S-rough sets are given: f- screen and - screen , and then puts forward - filter theorem, - filter theorem of knowledge. At last, the applications of knowledge separation are given according to - screen and - screen.展开更多
The concept of F-knowledge is presented by employing S-rough sets. By engrafting and penetrating between the F-knowledge generated by S-rough sets and the RSA algorithm, the security transmission and recognition of mu...The concept of F-knowledge is presented by employing S-rough sets. By engrafting and penetrating between the F-knowledge generated by S-rough sets and the RSA algorithm, the security transmission and recognition of multi-agent F-knowledge are proposed, which includes the security transmission of multi-agent F-knowledge with positive direction secret key and the security transmission of multi-agent F-knowledge with reverse direction secret key. Finally, the recognition criterion and the applications of F-knowledge are presented. The security of F-knowledge is a new application research direction of S-rough sets in information systems.展开更多
In previous researches on a model-based diagnostic system, the components are assumed mutually independent. Howerver , the assumption is not always the case because the information about whether a component is faulty ...In previous researches on a model-based diagnostic system, the components are assumed mutually independent. Howerver , the assumption is not always the case because the information about whether a component is faulty or not usually influences our knowledge about other components. Some experts may draw such a conclusion that 'if component m 1 is faulty, then component m 2 may be faulty too'. How can we use this experts' knowledge to aid the diagnosis? Based on Kohlas's probabilistic assumption-based reasoning method, we use Bayes networks to solve this problem. We calculate the posterior fault probability of the components in the observation state. The result is reasonable and reflects the effectiveness of the experts' knowledge.展开更多
To detect high frequency （HF） first-order sea echo spectra contaminated with ships, ionosphere interference, and other, a new characteristic-knowledge-aided detection method is proposed. With 2-D image features in r...To detect high frequency （HF） first-order sea echo spectra contaminated with ships, ionosphere interference, and other, a new characteristic-knowledge-aided detection method is proposed. With 2-D image features in range-Doppler spectrum, the trend of first-order sea echoes is extracted as indicative information by a multi-scale filter. Detection rules for both single and splitting first-order sea echoes are given based on the characteristic knowledge combining the indicative information with the global characteristics such as amplitude, symmetry, continuity, etc. Compared with the classical algorithms, the proposed method can detect and locate the first-order sea echo in the HF band more accurately especially in the environment with targets/clutters smearing. Experiments with real data verify the validity of the algorithm.展开更多
Differences in the structure and semantics of knowledge that is created and maintained by the various actors on the World Wide Web make its exchange and utilization a problematic task. This is an important issue facin...Differences in the structure and semantics of knowledge that is created and maintained by the various actors on the World Wide Web make its exchange and utilization a problematic task. This is an important issue facing organizations undertaking knowledge management initiatives. An XML-based and ontology-supported knowledge description language (KDL) is presented, which has three-tier structure (core KDL, extended KDL and complex KDL), and takes advantages of strong point of ontology, XML, description logics, frame-based systems. And then, the framework and XML based syntax of KDL are introduced, and the methods of translating KDL into first order logic (FOL) are presented. At last, the implementation of KDL on the Web is described, and the reasoning ability of KDL proved by experiment is illustrated in detail.展开更多
As expert systems technology has matured and migrated into mainstream computing, there arestill areas which are overlooked in education prospective knowledge engineers. This paper addresses this issue, and provides a ...As expert systems technology has matured and migrated into mainstream computing, there arestill areas which are overlooked in education prospective knowledge engineers. This paper addresses this issue, and provides a message to educators that expert and knowledge-based systems should be an importantstrategic science and technology for many organizations.展开更多
Using S-rough sets, this paper gives the concepts off-heredity knowledge and its heredity coefficient, and f-variation coefficient of knowledge; presents the theorem of f-attribute dependence of variation coefficient ...Using S-rough sets, this paper gives the concepts off-heredity knowledge and its heredity coefficient, and f-variation coefficient of knowledge; presents the theorem of f-attribute dependence of variation coefficient and the relation theorem of heredity-variation. The attribute dependence of f-variation coefficient and the relation of heredity-variation are important characteristics of S-rough sets. From such discussion, this paper puts forward the heredity mining off-knowledge and the algorithm of heredity mining, also gives its relative application.展开更多
The 21 st century is an era of knowledge, know le dge is said to be particularly important. Knowledge and information have become the economy’s primary raw material and its most important outcome. Under increas ingly...The 21 st century is an era of knowledge, know le dge is said to be particularly important. Knowledge and information have become the economy’s primary raw material and its most important outcome. Under increas ingly competitive pressure, many enterprises are examining how they can better m anage their knowledge. During the last years, another concept has gained increas ing interest: knowledge management. The emerging field of knowledge management a ddresses the broad processes of locating, organizing, transferring and more effi ciently using knowledge and expertise within an enterprise. An enterprise’s and its employees’ knowledge is regarded as the most important corporate capital in the arising global information society. Knowledge management therefore aims towa rds improving an enterprise’s ability to acquire, develop, preserve, distribute and use knowledge. This paper describes a conceptual model of knowledge manageme nt and innovation, focusing on analyzing the knowledge management and innovation process, trying to make knowledge more productive and create knowledge more eff iciently. In this paper, an integral and conceptual model of knowledge management and inno vation is presented first; then, the knowledge work process is analyzed, which i s conceptualized as a knowledge spiral; subsequently, knowledge management proce ss is conceptualized into knowledge development, knowledge acquisition, knowledg e transfer, knowledge sharing, knowledge utilization and knowledge evaluatio n, all of which can be conceptualized as a knowledge cycle; furthermore, the fac ilitating conditions for implementing knowledge management are analyzed; in the end, the input-output model of knowledge innovation is given as well as the mai n tools for assisting knowledge management are summarized.展开更多
基金supported by the National Social Science Foundation Major Project(22&ZD135)the National Social Science Fund National Emergency Management System Construction Research Project(20VYJ061).
文摘With the popularization of social media,public opi-nion information on emergencies spreads rapidly on the Internet,the impact of negative public opinions on an event has become more significant.Based on the organizational form of public opinion information,the knowledge graph is used to construct the knowledge base of public opinion risk cases on the emer-gency network.The emotion recognition model of negative pub-lic opinion information based on the bi-directional long short-term memory(BiLSTM)network is studied in the model layer design,and a linear discriminant analysis(LDA)topic extraction method combined with association rules is proposed to extract and mine the semantics of negative public opinion topics to real-ize further in-depth analysis of information topics.Focusing on public health emergencies,knowledge acquisition and knowl-edge processing of public opinion information are conducted,and the experimental results show that the knowledge graph framework based on the construction can facilitate in-depth theme evolution analysis of public opinion events,thus demon-strating important research significance for reducing online pub-lic opinion risks.
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.
基金the National Natural Science Foundation of China (Grants No. 12072090 and No.12302056) to provide fund for conducting experiments。
文摘Recently, high-precision trajectory prediction of ballistic missiles in the boost phase has become a research hotspot. This paper proposes a trajectory prediction algorithm driven by data and knowledge(DKTP) to solve this problem. Firstly, the complex dynamics characteristics of ballistic missile in the boost phase are analyzed in detail. Secondly, combining the missile dynamics model with the target gravity turning model, a knowledge-driven target three-dimensional turning(T3) model is derived. Then, the BP neural network is used to train the boost phase trajectory database in typical scenarios to obtain a datadriven state parameter mapping(SPM) model. On this basis, an online trajectory prediction framework driven by data and knowledge is established. Based on the SPM model, the three-dimensional turning coefficients of the target are predicted by using the current state of the target, and the state of the target at the next moment is obtained by combining the T3 model. Finally, simulation verification is carried out under various conditions. The simulation results show that the DKTP algorithm combines the advantages of data-driven and knowledge-driven, improves the interpretability of the algorithm, reduces the uncertainty, which can achieve high-precision trajectory prediction of ballistic missile in the boost phase.
文摘基于ISI Web of Knowledge平台,对8所纺织背景高校在2001—2011年间的科技论文进行了多角度的统计和分析,探讨了8所纺织背景高校近年来的学科发展现状和趋势,客观评价其学科研究特点和学术影响力,为纺织背景高校增强自身自然科学基础研究提供参考和帮助,并为其进一步发展提供可参考的定量依据.
文摘随着学校对图书馆经费投入的不断增加,数字环境下图书馆的合理使用变得越来越重要,其表现在数字资源上要有较多的用户访问和下载.从成员馆对比、登录情况、检索情况和成本等角度统计分析了东华大学ISI Web of Knowledge数据库使用情况,并分析讨论了读者群和多校区使用情况等,为图书馆电子资源订购提供有效依据.
文摘The conceptions of the knowledge screen generated by S-rough sets are given: f- screen and - screen , and then puts forward - filter theorem, - filter theorem of knowledge. At last, the applications of knowledge separation are given according to - screen and - screen.
基金supported partly by the Natural Science Foundation of Fujian Province of China(2009J01293)the Natural Science Foundation of Shandong Province of China(Y2007H02).
文摘The concept of F-knowledge is presented by employing S-rough sets. By engrafting and penetrating between the F-knowledge generated by S-rough sets and the RSA algorithm, the security transmission and recognition of multi-agent F-knowledge are proposed, which includes the security transmission of multi-agent F-knowledge with positive direction secret key and the security transmission of multi-agent F-knowledge with reverse direction secret key. Finally, the recognition criterion and the applications of F-knowledge are presented. The security of F-knowledge is a new application research direction of S-rough sets in information systems.
文摘In previous researches on a model-based diagnostic system, the components are assumed mutually independent. Howerver , the assumption is not always the case because the information about whether a component is faulty or not usually influences our knowledge about other components. Some experts may draw such a conclusion that 'if component m 1 is faulty, then component m 2 may be faulty too'. How can we use this experts' knowledge to aid the diagnosis? Based on Kohlas's probabilistic assumption-based reasoning method, we use Bayes networks to solve this problem. We calculate the posterior fault probability of the components in the observation state. The result is reasonable and reflects the effectiveness of the experts' knowledge.
文摘To detect high frequency （HF） first-order sea echo spectra contaminated with ships, ionosphere interference, and other, a new characteristic-knowledge-aided detection method is proposed. With 2-D image features in range-Doppler spectrum, the trend of first-order sea echoes is extracted as indicative information by a multi-scale filter. Detection rules for both single and splitting first-order sea echoes are given based on the characteristic knowledge combining the indicative information with the global characteristics such as amplitude, symmetry, continuity, etc. Compared with the classical algorithms, the proposed method can detect and locate the first-order sea echo in the HF band more accurately especially in the environment with targets/clutters smearing. Experiments with real data verify the validity of the algorithm.
文摘Differences in the structure and semantics of knowledge that is created and maintained by the various actors on the World Wide Web make its exchange and utilization a problematic task. This is an important issue facing organizations undertaking knowledge management initiatives. An XML-based and ontology-supported knowledge description language (KDL) is presented, which has three-tier structure (core KDL, extended KDL and complex KDL), and takes advantages of strong point of ontology, XML, description logics, frame-based systems. And then, the framework and XML based syntax of KDL are introduced, and the methods of translating KDL into first order logic (FOL) are presented. At last, the implementation of KDL on the Web is described, and the reasoning ability of KDL proved by experiment is illustrated in detail.
文摘As expert systems technology has matured and migrated into mainstream computing, there arestill areas which are overlooked in education prospective knowledge engineers. This paper addresses this issue, and provides a message to educators that expert and knowledge-based systems should be an importantstrategic science and technology for many organizations.
基金This project was supported by the National Natural Science Foundation of China (60364001), the Shandong ProvincialNatural Science Foundation of China (Y2004A04) and Fujian Provincial Education Foundation of China(JA04268).
文摘Using S-rough sets, this paper gives the concepts off-heredity knowledge and its heredity coefficient, and f-variation coefficient of knowledge; presents the theorem of f-attribute dependence of variation coefficient and the relation theorem of heredity-variation. The attribute dependence of f-variation coefficient and the relation of heredity-variation are important characteristics of S-rough sets. From such discussion, this paper puts forward the heredity mining off-knowledge and the algorithm of heredity mining, also gives its relative application.
文摘The 21 st century is an era of knowledge, know le dge is said to be particularly important. Knowledge and information have become the economy’s primary raw material and its most important outcome. Under increas ingly competitive pressure, many enterprises are examining how they can better m anage their knowledge. During the last years, another concept has gained increas ing interest: knowledge management. The emerging field of knowledge management a ddresses the broad processes of locating, organizing, transferring and more effi ciently using knowledge and expertise within an enterprise. An enterprise’s and its employees’ knowledge is regarded as the most important corporate capital in the arising global information society. Knowledge management therefore aims towa rds improving an enterprise’s ability to acquire, develop, preserve, distribute and use knowledge. This paper describes a conceptual model of knowledge manageme nt and innovation, focusing on analyzing the knowledge management and innovation process, trying to make knowledge more productive and create knowledge more eff iciently. In this paper, an integral and conceptual model of knowledge management and inno vation is presented first; then, the knowledge work process is analyzed, which i s conceptualized as a knowledge spiral; subsequently, knowledge management proce ss is conceptualized into knowledge development, knowledge acquisition, knowledg e transfer, knowledge sharing, knowledge utilization and knowledge evaluatio n, all of which can be conceptualized as a knowledge cycle; furthermore, the fac ilitating conditions for implementing knowledge management are analyzed; in the end, the input-output model of knowledge innovation is given as well as the mai n tools for assisting knowledge management are summarized.
