Taking CNKI database as the data source and measuring visual map analysis tool Citespace as auxiliary tool,domestic 843 articles in recent 15 years are analyzed,and visualization maps such as time line analysis,instit...Taking CNKI database as the data source and measuring visual map analysis tool Citespace as auxiliary tool,domestic 843 articles in recent 15 years are analyzed,and visualization maps such as time line analysis,institutional cooperation network analysis,author collaboration network analysis,keyword co-occurrence,and emergent words analysis are drawn.Combined with the literature content analysis,four hot spots in the research field of landscape architecture microclimate in China are obtained,namely ENVI-MET,comfort,design strategy and urban green space.The research trend is thermal comfort,human body comfort and winter city.The research results can provide reference for the research on domestic garden microclimate.展开更多
Objective To study the research status,research hotspots and development trends in the field of real-world data(RWD)through social network analysis and knowledge graph analysis.Methods RWD of the past 10 years were re...Objective To study the research status,research hotspots and development trends in the field of real-world data(RWD)through social network analysis and knowledge graph analysis.Methods RWD of the past 10 years were retrieved,and literature metrological analysis was made by using UCINET and CiteSpace from CNKI.Results and Conclusion The frequency and centrality of related keywords such as real-world study,hospital information system(HIS),drug combination,data mining and TCM are high.The clusters labeled as clinical medication and RWD contain more keywords.In recent 4 years,there are more articles involving the keywords of data specification,data authenticity,data security and information security.Among them,compound Kushen injection,HIS database and RWD are the top three keywords.It is a long-term research hotspot for Chinese and western medicine to use HIS to study clinical medication,clinical characteristics,diseases and injections.Besides,the research of RWD database has changed from construction to standardized collection and governance,which can make RWD effective.Data authenticity,data security and information security will become the new hotspots in the research of RWD.展开更多
Using the advantages of web crawlers in data collection and distributed storage technologies,we accessed to a wealth of forestry-related data.Combined with the mature big data technology at its present stage,Hadoop...Using the advantages of web crawlers in data collection and distributed storage technologies,we accessed to a wealth of forestry-related data.Combined with the mature big data technology at its present stage,Hadoop's distributed system was selected to solve the storage problem of massive forestry big data and the memory-based Spark computing framework to realize real-time and fast processing of data.The forestry data contains a wealth of information,and mining this information is of great significance for guiding the development of forestry.We conducts co-word and cluster analyses on the keywords of forestry data,extracts the rules hidden in the data,analyzes the research hotspots more accurately,grasps the evolution trend of subject topics,and plays an important role in promoting the research and development of subject areas.The co-word analysis and clustering algorithm have important practical significance for the topic structure,research hotspot or development trend in the field of forestry research.Distributed storage framework and parallel computing have greatly improved the performance of data mining algorithms.Therefore,the forestry big data mining system by big data technology has important practical significance for promoting the development of intelligent forestry.展开更多
Generally,knowledge extraction technology is used to obtain nodes and relationships of unstructured data and structured data,and then the data fuse with the original knowledge graph to achieve the extension of the kno...Generally,knowledge extraction technology is used to obtain nodes and relationships of unstructured data and structured data,and then the data fuse with the original knowledge graph to achieve the extension of the knowledge graph.Because the concepts and knowledge structures expressed on the Internet have problems of multi-source heterogeneity and low accuracy,it is usually difficult to achieve a good effect simply by using knowledge extraction technology.Considering that domain knowledge is highly dependent on the relevant expert knowledge,the method of this paper try to expand the domain knowledge through the crowdsourcing method.The method split the domain knowledge system into subgraph of knowledge according to corresponding concept,form subtasks with moderate granularity,and use the crowdsourcing technology for the acquisition and integration of knowledge subgraph to improve the knowledge system.展开更多
This study employed the bibliometric software CiteSpace 6.1.R6 to analyze the correlation between thermal infrared,spectral remote sensing technology,and the estimation of economic forest water stress.It aimed to revi...This study employed the bibliometric software CiteSpace 6.1.R6 to analyze the correlation between thermal infrared,spectral remote sensing technology,and the estimation of economic forest water stress.It aimed to review the development and current status of this field,as well as to identify future research trends.A search was conducted on the China National Knowledge Infrastructure(CNKI)database using the keyword“water stress”for relevant studies from 2003 to 2023.The visual analysis function of CNKI was used to generate the distribution of annual publication volume,and CiteSpace 6.1.R6 was utilized to create network maps illustrating collaboration among authors and institutions.The study also analyzed the hotspots and frontiers of economic forest water stress.As a result,a total of 6664 academic journal articles related to water stress were retrieved.Considerable collaboration networks were observed among scholars and institutions,with a focus on using crown temperature monitoring to diagnose crop water stress.Based on the research findings,it was evident that the primary research trend involved the use of thermal infrared and spectral remote sensing technology for estimating water stress,making it a future research hotspot.展开更多
Objective: This study visualizes and analyzes the current status, hotspots, and frontiers of cardiac rehabilitation for patients with Coronary Heart Disease (CHD) over the past decade (2012.01-2022.12), and explores t...Objective: This study visualizes and analyzes the current status, hotspots, and frontiers of cardiac rehabilitation for patients with Coronary Heart Disease (CHD) over the past decade (2012.01-2022.12), and explores the future development trend and research direction of the CR for CHD patients in China. Methods: Relevant literature was searched, screened and downloaded from the Web of Science (WOS) database, and bibliometric and visualization analyses were performed using CiteSpace VI software. Results: Through the search and screening of related literature, 2443 English articles were finally included. Among them, most of the Chinese publishers were mainly universities and had less connection with each other, while the foreign publishers were mainly universities and medical institutions in the United States and Europe, and had close connection with each other. The research content of Chinese scholars mainly focuses on the assessment of patients’ life and psychological status, as well as the assessment of cardiac function. Foreign research focuses on physical training assessment, disease perception, etc. Conclusion: Through visualizing relevant research with CiteSpace VI software in the form of a knowledge map, the research frontiers and trends in the field of cardiac rehabilitation for coronary heart disease patients in China and abroad can be discovered more intuitively. Compared with foreign research, the development of cardiac rehabilitation for coronary heart disease patients in China is relatively slow and insufficient, and institutions lack cooperation. In the future, China should accelerate the connection between regions in the field of cardiac rehabilitation and develop a cardiac rehabilitation model suitable for coronary heart disease patients in China with its own characteristics.展开更多
Aspect-oriented sentiment analysis is a meticulous sentiment analysis task that aims to analyse the sentiment polarity of specific aspects. Most of the current research builds graph convolutional networks based on dep...Aspect-oriented sentiment analysis is a meticulous sentiment analysis task that aims to analyse the sentiment polarity of specific aspects. Most of the current research builds graph convolutional networks based on dependent syntactic trees, which improves the classification performance of the models to some extent. However, the technical limitations of dependent syntactic trees can introduce considerable noise into the model. Meanwhile, it is difficult for a single graph convolutional network to aggregate both semantic and syntactic structural information of nodes, which affects the final sentence classification. To cope with the above problems, this paper proposes a bi-channel graph convolutional network model. The model introduces a phrase structure tree and transforms it into a hierarchical phrase matrix. The adjacency matrix of the dependent syntactic tree and the hierarchical phrase matrix are combined as the initial matrix of the graph convolutional network to enhance the syntactic information. The semantic information feature representations of the sentences are obtained by the graph convolutional network with a multi-head attention mechanism and fused to achieve complementary learning of dual-channel features. Experimental results show that the model performs well and improves the accuracy of sentiment classification on three public benchmark datasets, namely Rest14, Lap14 and Twitter.展开更多
Connected and autonomous vehicle formation(CAVF)technology is considerably important for improving transportation efficiency,optimizing traffic flow,and reduc-ing energy consumption.Despite the extensive research con-...Connected and autonomous vehicle formation(CAVF)technology is considerably important for improving transportation efficiency,optimizing traffic flow,and reduc-ing energy consumption.Despite the extensive research con-ducted on trajectory tracking control and other aspects of CAVF,the quality of the extant literature varies consider-ably,and research content remains scattered.To better pro-mote the sustainable and healthy development of the CAVF field,this paper employs the mapping knowledge domain(MKD)methodology to comprehensively review and visual-ize the current research status in this domain.Based on this review,research themes,hotspots,research challenges,and future development directions are proposed.The findings suggest that the research on CAVF can be categorized into three primary developmental stages.China and the United States are the primary countries conducting CAVF research.There is a positive correlation between economic develop-ment and the generation of scientific research outcomes.Re-search institutions are predominantly concentrated in univer-sities.The field exhibits significant interdisciplinary and inte-gration characteristics,forming key research personnel and teams.It is expected that future research will concentrate on topics such as deep learning,trajectory optimization,energy management strategy,mixed vehicle platoon,and other re-lated subjects.Research on cognition-driven intelligent for-mation decision-making mechanisms,resilience-oriented for-mation safety assurance systems,multiobjective collabora-tive formation optimization strategies,and digital twin-driven formation system validation platforms represents key future development directions.展开更多
Social engineering has posed a serious threat to cyberspace security.To protect against social engineering attacks,a fundamental work is to know what constitutes social engineering.This paper first develops a domain o...Social engineering has posed a serious threat to cyberspace security.To protect against social engineering attacks,a fundamental work is to know what constitutes social engineering.This paper first develops a domain ontology of social engineering in cybersecurity and conducts ontology evaluation by its knowledge graph application.The domain ontology defines 11 concepts of core entities that significantly constitute or affect social engineering domain,together with 22 kinds of relations describing how these entities related to each other.It provides a formal and explicit knowledge schema to understand,analyze,reuse and share domain knowledge of social engineering.Furthermore,this paper builds a knowledge graph based on 15 social engineering attack incidents and scenarios.7 knowledge graph application examples(in 6 analysis patterns)demonstrate that the ontology together with knowledge graph is useful to 1)understand and analyze social engineering attack scenario and incident,2)find the top ranked social engineering threat elements(e.g.the most exploited human vulnerabilities and most used attack mediums),3)find potential social engineering threats to victims,4)find potential targets for social engineering attackers,5)find potential attack paths from specific attacker to specific target,and 6)analyze the same origin attacks.展开更多
Traditional Chinese medicine(TCM)serves as a treasure trove of ancient knowledge,holding a crucial position in the medical field.However,the exploration of TCM's extensive information has been hindered by challeng...Traditional Chinese medicine(TCM)serves as a treasure trove of ancient knowledge,holding a crucial position in the medical field.However,the exploration of TCM's extensive information has been hindered by challenges related to data standardization,completeness,and accuracy,primarily due to the decen-tralized distribution of TCM resources.To address these issues,we developed a platform for TCM knowledge discovery(TCMKD,https://cbcb.cdutcm.edu.cn/TCMKD/).Seven types of data,including syndromes,formulas,Chinese patent drugs(CPDs),Chinese medicinal materials(CMMs),ingredients,targets,and diseases,were manually proofread and consolidated within TCMKD.To strengthen the integration of TCM with modern medicine,TCMKD employs analytical methods such as TCM data mining,enrichment analysis,and network localization and separation.These tools help elucidate the molecular-level commonalities between TCM and contemporary scientific insights.In addition to its analytical capabilities,a quick question and answer(Q&A)system is also embedded within TCMKD to query the database efficiently,thereby improving the interactivity of the platform.The platform also provides a TCM text annotation tool,offering a simple and efficient method for TCM text mining.Overall,TCMKD not only has the potential to become a pivotal repository for TCM,delving into the pharmaco-logical foundations of TCM treatments,but its flexible embedded tools and algorithms can also be applied to the study of other traditional medical systems,extending beyond just TCM.展开更多
[Objectives]Based on bibliometric methods,the evolution path and knowledge structure of shampoo product research in China were systematically analyzed,with a focus on the composition,efficacy,and mechanisms of traditi...[Objectives]Based on bibliometric methods,the evolution path and knowledge structure of shampoo product research in China were systematically analyzed,with a focus on the composition,efficacy,and mechanisms of traditional Chinese medicine shampoos,aiming to reveal the shifting patterns of core technological focuses at different stages and identify key future research directions.[Methods]Using a sample of 515 publications from CNKI journals between 2005 and 2025,CiteSpace 6.3.R1 was employed to construct multi-dimensional networks of authors,institutions,and keywords.Burst detection,keyword and cluster analyses,and time zone mapping were applied to track disciplinary dynamics.[Results]The analysis on the annual number of publications indicated that research on shampoo products underwent multiple phases including initial development,growth,fluctuation,peak,and adjustment from 2005 to 2025,with an overall upward trend.The significant differences between the collaboration network density of core authors and the strength of institutional cooperation indicated a need for academia to enhance cross-institutional collaborative innovation mechanisms.Keyword clustering analysis and co-occurrence mapping revealed that the research on traditional Chinese medicine shampoo products,known for their natural,mild,and non-irritating characteristics,demonstrates notable advantages in dandruff removal,anti-hair loss,hair growth,and scalp health management,which have become current research hotspots,providing data-driven decision-making support for technological upgrading and industry-academia-research integration in the field.[Conclusions]The bibliometric analysis based on 515 publications indicates that the overall development direction of shampoo products will comprehensively advance toward refined efficacy and personalized customization,greener and more natural ingredients,technological innovation and industry-academia-research collaboration,market segmentation and diversified development,as well as safety and efficacy evaluation.This study provides theoretical support for the innovation of specialized traditional Chinese medicine shampoo products.展开更多
Graphical methods are used for construction.Data analysis and visualization are an important area of applications of big data.At the same time,visual analysis is also an important method for big data analysis.Data vis...Graphical methods are used for construction.Data analysis and visualization are an important area of applications of big data.At the same time,visual analysis is also an important method for big data analysis.Data visualization refers to data that is presented in a visual form,such as a chart or map,to help people understand the meaning of the data.Data visualization helps people extract meaning from data quickly and easily.Visualization can be used to fully demonstrate the patterns,trends,and dependencies of your data,which can be found in other displays.Big data visualization analysis combines the advantages of computers,which can be static or interactive,interactive analysis methods and interactive technologies,which can directly help people and effectively understand the information behind big data.It is indispensable in the era of big data visualization,and it can be very intuitive if used properly.Graphical analysis also found that valuable information becomes a powerful tool in complex data relationships,and it represents a significant business opportunity.With the rise of big data,important technologies suitable for dealing with complex relationships have emerged.Graphics come in a variety of shapes and sizes for a variety of business problems.Graphic analysis is first in the visualization.The step is to get the right data and answer the goal.In short,to choose the right method,you must understand each relative strengths and weaknesses and understand the data.Key steps to get data:target;collect;clean;connect.展开更多
Purpose: This paper explores a method of knowledge discovery by visualizing and analyzing co-occurrence relations among three or more entities in collections of journal articles.Design/methodology/approach: A variety ...Purpose: This paper explores a method of knowledge discovery by visualizing and analyzing co-occurrence relations among three or more entities in collections of journal articles.Design/methodology/approach: A variety of methods such as the model construction,system analysis and experiments are used. The author has improved Morris' crossmapping technique and developed a technique for directly describing,visualizing and analyzing co-occurrence relations among three or more entities in collections of journal articles.Findings: The visualization tools and the knowledge discovery method can efficiently reveal the multiple co-occurrence relations among three entities in collections of journal papers. It can reveal more and in-depth information than analyzing co-occurrence relations between two entities. Therefore,this method can be used for mapping knowledge domain that is manifested in association with the entities from multi-dimensional perspectives and in an all-round way.Research limitations: The technique could only be used to analyze co-occurrence relations of less than three entities at present.Practical implications: This research has expanded the study scope of co-occurrence analysis.The research result has provided a theoretical support for co-occurrence analysis.Originality/value: There has not been a systematic study on co-occurrence relations among multiple entities in collections of journal articles. This research defines multiple co-occurrence and the research scope,develops the visualization analysis tool and designs the analysis model of the knowledge discovery method.展开更多
In recent years,the field of cold chain logistics for fruits and vegetables has emerged as a significant topic in academic research.This study adopts a bibliometric approach and utilizes the visual analysis tool CiteS...In recent years,the field of cold chain logistics for fruits and vegetables has emerged as a significant topic in academic research.This study adopts a bibliometric approach and utilizes the visual analysis tool CiteSpace to systematically investigate the progress of domestic research in this area.Based on 209 core articles retrieved from the CNKI(China National Knowledge Infrastructure)database from January 2007 to May 2024,the study constructs multi-dimensional knowledge graphs—including discipline co-occurrence networks,author collaboration networks,and keyword timezone maps.The analysis reveals several key findings:there is a marked upward trend in the annual number of publications,research hotspots have evolved in phases,and core research areas concentrate on the optimization of cold chain logistics systems,innovations in preservation technologies for fruits and vegetables,and the construction of agricultural product logistics networks.It is worth noting that quality control of fruits and vegetables,along with related technological challenges,may become prominent directions for future research.展开更多
Purpose: The evolution of the socio-cognitive structure of the field of knowledge management(KM) during the period 1986–2015 is described. Design/methodology/approach: Records retrieved from Web of Science were submi...Purpose: The evolution of the socio-cognitive structure of the field of knowledge management(KM) during the period 1986–2015 is described. Design/methodology/approach: Records retrieved from Web of Science were submitted to author co-citation analysis(ACA) following a longitudinal perspective as of the following time slices: 1986–1996, 1997–2006, and 2007–2015. The top 10% of most cited first authors by sub-periods were mapped in bibliometric networks in order to interpret the communities formed and their relationships.Findings: KM is a homogeneous field as indicated by networks results. Nine classical authors are identified since they are highly co-cited in each sub-period, highlighting Ikujiro Nonaka as the most influential authors in the field. The most significant communities in KM are devoted to strategic management, KM foundations, organisational learning and behaviour, and organisational theories. Major trends in the evolution of the intellectual structure of KM evidence a technological influence in 1986–1996, a strategic influence in 1997–2006, and finally a sociological influence in 2007–2015.Research limitations: Describing a field from a single database can offer biases in terms of output coverage. Likewise, the conference proceedings and books were not used and the analysis was only based on first authors. However, the results obtained can be very useful to understand the evolution of KM research.Practical implications: These results might be useful for managers and academicians to understand the evolution of KM field and to(re)define research activities and organisational projects.Originality/value: The novelty of this paper lies in considering ACA as a bibliometric technique to study KM research. In addition, our investigation has a wider time coverage than earlier articles.展开更多
BACKGROUND In the rapidly evolving landscape of psychiatric research,2023 marked another year of significant progress globally,with the World Journal of Psychiatry(WJP)experiencing notable expansion and influence.AIM ...BACKGROUND In the rapidly evolving landscape of psychiatric research,2023 marked another year of significant progress globally,with the World Journal of Psychiatry(WJP)experiencing notable expansion and influence.AIM To conduct a comprehensive visualization and analysis of the articles published in the WJP throughout 2023.By delving into these publications,the aim is to deter-mine the valuable insights that can illuminate pathways for future research endeavors in the field of psychiatry.METHODS A selection process led to the inclusion of 107 papers from the WJP published in 2023,forming the dataset for the analysis.Employing advanced visualization techniques,this study mapped the knowledge domains represented in these papers.RESULTS The findings revealed a prevalent focus on key topics such as depression,mental health,anxiety,schizophrenia,and the impact of coronavirus disease 2019.Additionally,through keyword clustering,it became evident that these papers were predominantly focused on exploring mental health disorders,depression,anxiety,schizophrenia,and related factors.Noteworthy contributions hailed authors in regions such as China,the United Kingdom,United States,and Turkey.Particularly,the paper garnered the highest number of citations,while the American Psychiatric Association was the most cited reference.CONCLUSION It is recommended that the WJP continue in its efforts to enhance the quality of papers published in the field of psychiatry.Additionally,there is a pressing need to delve into the potential applications of digital interventions and artificial intelligence within the discipline.展开更多
The development of the information age and globalization has challenged the training of technical talents in the 21st century, and the information media and technical skills are becoming increasingly important. As a c...The development of the information age and globalization has challenged the training of technical talents in the 21st century, and the information media and technical skills are becoming increasingly important. As a creative sharing form of multimedia, the digital storytelling is being concerned by more and more educators because of its discipline applicability and media technology enhancing ability. In this study, the information visualization software, i.e. CiteSpace was applied to visualize and analyze the researches on digital storytelling from the aspects of key articles and citation hotspots, and make a review on the research status of the digital storytelling in the education fields, such as promoting language learning, and helping students develop the 21 st century skills.展开更多
The aim of the paper is to identify and explore leading thematic areas within the research field related to Business Schools Accreditation in China.Based on data from the China National Knowledge Infrastructure(CNKI)d...The aim of the paper is to identify and explore leading thematic areas within the research field related to Business Schools Accreditation in China.Based on data from the China National Knowledge Infrastructure(CNKI)database,the keywords frequency was analyzed,and the theory of mapping knowledge domain was used to visualize the keywords co-occurrence network to make further research of the heated issues.The findings indicate that the research scope involved in business school accreditation research is broad,and research content focus on teaching,management,talent cultivation.According to the results of keywords co-occurrence analysis of different stages,AACSB,AACSB Accreditation,international accreditation,business school,AOL,internationalization,accreditation are the most important issues to business school research in China,given their position and role in the research network.The paper generates the added value mainly from the point of view of theory development.展开更多
The aim of the paper is to identify and explore leading development situation within the research field related to student classroom engagement.Using knowledge mapping tools,this paper conducted the visualization anal...The aim of the paper is to identify and explore leading development situation within the research field related to student classroom engagement.Using knowledge mapping tools,this paper conducted the visualization analysis on internationalliteraturein relation to student classroom engagementfrom the Web of Science databases.By combination of the statistical data and visualizationmapping,this paper studied on the research relationship networks and status for the co-authors'countries/institutions,co-citation documents/journalsand co-occurring keywordsbased on the sample datafromliterature.The results indicate that the number ofpublished papershasincreased obviously and expanded graduallysince 2000.Main countries and institutions of researches were the UnitedStates,Australia,United Kingdom,Canada and China in order,and these countries had intense collaboration.The theoretical basis of the research come from education and teaching,psychology.The hotspots of researches fromthe global literature coveredvarious fields including achievement,motivation,behavior,education,performance.As a result of the multidisciplinary integration,many relevant internationalresearch constantly expanded the research scopes,which promoted the combination and development of theories.展开更多
基金Sponsored by the National Natural Science Foundation of China(Youth Program)(51908063)。
文摘Taking CNKI database as the data source and measuring visual map analysis tool Citespace as auxiliary tool,domestic 843 articles in recent 15 years are analyzed,and visualization maps such as time line analysis,institutional cooperation network analysis,author collaboration network analysis,keyword co-occurrence,and emergent words analysis are drawn.Combined with the literature content analysis,four hot spots in the research field of landscape architecture microclimate in China are obtained,namely ENVI-MET,comfort,design strategy and urban green space.The research trend is thermal comfort,human body comfort and winter city.The research results can provide reference for the research on domestic garden microclimate.
文摘Objective To study the research status,research hotspots and development trends in the field of real-world data(RWD)through social network analysis and knowledge graph analysis.Methods RWD of the past 10 years were retrieved,and literature metrological analysis was made by using UCINET and CiteSpace from CNKI.Results and Conclusion The frequency and centrality of related keywords such as real-world study,hospital information system(HIS),drug combination,data mining and TCM are high.The clusters labeled as clinical medication and RWD contain more keywords.In recent 4 years,there are more articles involving the keywords of data specification,data authenticity,data security and information security.Among them,compound Kushen injection,HIS database and RWD are the top three keywords.It is a long-term research hotspot for Chinese and western medicine to use HIS to study clinical medication,clinical characteristics,diseases and injections.Besides,the research of RWD database has changed from construction to standardized collection and governance,which can make RWD effective.Data authenticity,data security and information security will become the new hotspots in the research of RWD.
基金grants from the Fundamental Research Funds for the Central Universities(Grant No.2572018BH02)Special Funds for Scientific Research in the Forestry Public Welfare Industry(Grant Nos.201504307-03)。
文摘Using the advantages of web crawlers in data collection and distributed storage technologies,we accessed to a wealth of forestry-related data.Combined with the mature big data technology at its present stage,Hadoop's distributed system was selected to solve the storage problem of massive forestry big data and the memory-based Spark computing framework to realize real-time and fast processing of data.The forestry data contains a wealth of information,and mining this information is of great significance for guiding the development of forestry.We conducts co-word and cluster analyses on the keywords of forestry data,extracts the rules hidden in the data,analyzes the research hotspots more accurately,grasps the evolution trend of subject topics,and plays an important role in promoting the research and development of subject areas.The co-word analysis and clustering algorithm have important practical significance for the topic structure,research hotspot or development trend in the field of forestry research.Distributed storage framework and parallel computing have greatly improved the performance of data mining algorithms.Therefore,the forestry big data mining system by big data technology has important practical significance for promoting the development of intelligent forestry.
文摘Generally,knowledge extraction technology is used to obtain nodes and relationships of unstructured data and structured data,and then the data fuse with the original knowledge graph to achieve the extension of the knowledge graph.Because the concepts and knowledge structures expressed on the Internet have problems of multi-source heterogeneity and low accuracy,it is usually difficult to achieve a good effect simply by using knowledge extraction technology.Considering that domain knowledge is highly dependent on the relevant expert knowledge,the method of this paper try to expand the domain knowledge through the crowdsourcing method.The method split the domain knowledge system into subgraph of knowledge according to corresponding concept,form subtasks with moderate granularity,and use the crowdsourcing technology for the acquisition and integration of knowledge subgraph to improve the knowledge system.
基金the Inner Mongolia Natural Science Foundation(2023MS06002)the Scientific Research Project of Higher Education Institutions of Inner Mongolia Autonomous Region(NJZZ22509)+1 种基金the Development Project of Young Scientific and Technological Talents(Innovative Teams)of Inner Mongolia Autonomous Region 2023(NHGIRT2312)the Project of Research and Practice on Teaching Reform of Graduate Education of Inner Mongolia Autonomous Region(JGCG2023049)were funded.
文摘This study employed the bibliometric software CiteSpace 6.1.R6 to analyze the correlation between thermal infrared,spectral remote sensing technology,and the estimation of economic forest water stress.It aimed to review the development and current status of this field,as well as to identify future research trends.A search was conducted on the China National Knowledge Infrastructure(CNKI)database using the keyword“water stress”for relevant studies from 2003 to 2023.The visual analysis function of CNKI was used to generate the distribution of annual publication volume,and CiteSpace 6.1.R6 was utilized to create network maps illustrating collaboration among authors and institutions.The study also analyzed the hotspots and frontiers of economic forest water stress.As a result,a total of 6664 academic journal articles related to water stress were retrieved.Considerable collaboration networks were observed among scholars and institutions,with a focus on using crown temperature monitoring to diagnose crop water stress.Based on the research findings,it was evident that the primary research trend involved the use of thermal infrared and spectral remote sensing technology for estimating water stress,making it a future research hotspot.
文摘Objective: This study visualizes and analyzes the current status, hotspots, and frontiers of cardiac rehabilitation for patients with Coronary Heart Disease (CHD) over the past decade (2012.01-2022.12), and explores the future development trend and research direction of the CR for CHD patients in China. Methods: Relevant literature was searched, screened and downloaded from the Web of Science (WOS) database, and bibliometric and visualization analyses were performed using CiteSpace VI software. Results: Through the search and screening of related literature, 2443 English articles were finally included. Among them, most of the Chinese publishers were mainly universities and had less connection with each other, while the foreign publishers were mainly universities and medical institutions in the United States and Europe, and had close connection with each other. The research content of Chinese scholars mainly focuses on the assessment of patients’ life and psychological status, as well as the assessment of cardiac function. Foreign research focuses on physical training assessment, disease perception, etc. Conclusion: Through visualizing relevant research with CiteSpace VI software in the form of a knowledge map, the research frontiers and trends in the field of cardiac rehabilitation for coronary heart disease patients in China and abroad can be discovered more intuitively. Compared with foreign research, the development of cardiac rehabilitation for coronary heart disease patients in China is relatively slow and insufficient, and institutions lack cooperation. In the future, China should accelerate the connection between regions in the field of cardiac rehabilitation and develop a cardiac rehabilitation model suitable for coronary heart disease patients in China with its own characteristics.
文摘Aspect-oriented sentiment analysis is a meticulous sentiment analysis task that aims to analyse the sentiment polarity of specific aspects. Most of the current research builds graph convolutional networks based on dependent syntactic trees, which improves the classification performance of the models to some extent. However, the technical limitations of dependent syntactic trees can introduce considerable noise into the model. Meanwhile, it is difficult for a single graph convolutional network to aggregate both semantic and syntactic structural information of nodes, which affects the final sentence classification. To cope with the above problems, this paper proposes a bi-channel graph convolutional network model. The model introduces a phrase structure tree and transforms it into a hierarchical phrase matrix. The adjacency matrix of the dependent syntactic tree and the hierarchical phrase matrix are combined as the initial matrix of the graph convolutional network to enhance the syntactic information. The semantic information feature representations of the sentences are obtained by the graph convolutional network with a multi-head attention mechanism and fused to achieve complementary learning of dual-channel features. Experimental results show that the model performs well and improves the accuracy of sentiment classification on three public benchmark datasets, namely Rest14, Lap14 and Twitter.
基金The National Natural Science Foundation of China (No. 52302373, 52472317)the Natural Science Foundation of Beijing (No. L231023)the Beijing Nova Program (No. 20230484443)。
文摘Connected and autonomous vehicle formation(CAVF)technology is considerably important for improving transportation efficiency,optimizing traffic flow,and reduc-ing energy consumption.Despite the extensive research con-ducted on trajectory tracking control and other aspects of CAVF,the quality of the extant literature varies consider-ably,and research content remains scattered.To better pro-mote the sustainable and healthy development of the CAVF field,this paper employs the mapping knowledge domain(MKD)methodology to comprehensively review and visual-ize the current research status in this domain.Based on this review,research themes,hotspots,research challenges,and future development directions are proposed.The findings suggest that the research on CAVF can be categorized into three primary developmental stages.China and the United States are the primary countries conducting CAVF research.There is a positive correlation between economic develop-ment and the generation of scientific research outcomes.Re-search institutions are predominantly concentrated in univer-sities.The field exhibits significant interdisciplinary and inte-gration characteristics,forming key research personnel and teams.It is expected that future research will concentrate on topics such as deep learning,trajectory optimization,energy management strategy,mixed vehicle platoon,and other re-lated subjects.Research on cognition-driven intelligent for-mation decision-making mechanisms,resilience-oriented for-mation safety assurance systems,multiobjective collabora-tive formation optimization strategies,and digital twin-driven formation system validation platforms represents key future development directions.
基金the National Key Research and Development Program of China(2017YFB0802804)the Joint Fund of the National Natural Science Foundation of China(U1766215).
文摘Social engineering has posed a serious threat to cyberspace security.To protect against social engineering attacks,a fundamental work is to know what constitutes social engineering.This paper first develops a domain ontology of social engineering in cybersecurity and conducts ontology evaluation by its knowledge graph application.The domain ontology defines 11 concepts of core entities that significantly constitute or affect social engineering domain,together with 22 kinds of relations describing how these entities related to each other.It provides a formal and explicit knowledge schema to understand,analyze,reuse and share domain knowledge of social engineering.Furthermore,this paper builds a knowledge graph based on 15 social engineering attack incidents and scenarios.7 knowledge graph application examples(in 6 analysis patterns)demonstrate that the ontology together with knowledge graph is useful to 1)understand and analyze social engineering attack scenario and incident,2)find the top ranked social engineering threat elements(e.g.the most exploited human vulnerabilities and most used attack mediums),3)find potential social engineering threats to victims,4)find potential targets for social engineering attackers,5)find potential attack paths from specific attacker to specific target,and 6)analyze the same origin attacks.
基金supported by Natural Science Foundation of Sichuan,China(Grant No.:2024ZDZX0019).
文摘Traditional Chinese medicine(TCM)serves as a treasure trove of ancient knowledge,holding a crucial position in the medical field.However,the exploration of TCM's extensive information has been hindered by challenges related to data standardization,completeness,and accuracy,primarily due to the decen-tralized distribution of TCM resources.To address these issues,we developed a platform for TCM knowledge discovery(TCMKD,https://cbcb.cdutcm.edu.cn/TCMKD/).Seven types of data,including syndromes,formulas,Chinese patent drugs(CPDs),Chinese medicinal materials(CMMs),ingredients,targets,and diseases,were manually proofread and consolidated within TCMKD.To strengthen the integration of TCM with modern medicine,TCMKD employs analytical methods such as TCM data mining,enrichment analysis,and network localization and separation.These tools help elucidate the molecular-level commonalities between TCM and contemporary scientific insights.In addition to its analytical capabilities,a quick question and answer(Q&A)system is also embedded within TCMKD to query the database efficiently,thereby improving the interactivity of the platform.The platform also provides a TCM text annotation tool,offering a simple and efficient method for TCM text mining.Overall,TCMKD not only has the potential to become a pivotal repository for TCM,delving into the pharmaco-logical foundations of TCM treatments,but its flexible embedded tools and algorithms can also be applied to the study of other traditional medical systems,extending beyond just TCM.
基金Supported by Undergraduate Innovation and Entrepreneurship Program of Faculty of Chinese Medicine Science of Guangxi University of Chinese Medicine (Autonomous Region Level) (S202413643051)Guangxi First-class Discipline Construction Project (GJKY[2022]1).
文摘[Objectives]Based on bibliometric methods,the evolution path and knowledge structure of shampoo product research in China were systematically analyzed,with a focus on the composition,efficacy,and mechanisms of traditional Chinese medicine shampoos,aiming to reveal the shifting patterns of core technological focuses at different stages and identify key future research directions.[Methods]Using a sample of 515 publications from CNKI journals between 2005 and 2025,CiteSpace 6.3.R1 was employed to construct multi-dimensional networks of authors,institutions,and keywords.Burst detection,keyword and cluster analyses,and time zone mapping were applied to track disciplinary dynamics.[Results]The analysis on the annual number of publications indicated that research on shampoo products underwent multiple phases including initial development,growth,fluctuation,peak,and adjustment from 2005 to 2025,with an overall upward trend.The significant differences between the collaboration network density of core authors and the strength of institutional cooperation indicated a need for academia to enhance cross-institutional collaborative innovation mechanisms.Keyword clustering analysis and co-occurrence mapping revealed that the research on traditional Chinese medicine shampoo products,known for their natural,mild,and non-irritating characteristics,demonstrates notable advantages in dandruff removal,anti-hair loss,hair growth,and scalp health management,which have become current research hotspots,providing data-driven decision-making support for technological upgrading and industry-academia-research integration in the field.[Conclusions]The bibliometric analysis based on 515 publications indicates that the overall development direction of shampoo products will comprehensively advance toward refined efficacy and personalized customization,greener and more natural ingredients,technological innovation and industry-academia-research collaboration,market segmentation and diversified development,as well as safety and efficacy evaluation.This study provides theoretical support for the innovation of specialized traditional Chinese medicine shampoo products.
基金This research work is supported by Hunan Provincial Education Science 13th Five Year Plan(Grant No.XJK016BXX001)Social Science Foundation of Hunan Province(Grant No.17YBA049)+2 种基金Hunan Provincial Natural Science Foundation of China(Grant No.2017JJ2016)National Students’platform for innovation and entrepreneurship training(Grant No.201811532010)The work is also supported by Open foundation for University Innovation Platform from Hunan Province,China(Grand No.16K013)and the 2011 Collaborative Innovation Center of Big Data for Financial and Economical Asset Development and Utility in Universities of Hunan Province.We also thank the anonymous reviewers for their valuable comments and insightful suggestions.
文摘Graphical methods are used for construction.Data analysis and visualization are an important area of applications of big data.At the same time,visual analysis is also an important method for big data analysis.Data visualization refers to data that is presented in a visual form,such as a chart or map,to help people understand the meaning of the data.Data visualization helps people extract meaning from data quickly and easily.Visualization can be used to fully demonstrate the patterns,trends,and dependencies of your data,which can be found in other displays.Big data visualization analysis combines the advantages of computers,which can be static or interactive,interactive analysis methods and interactive technologies,which can directly help people and effectively understand the information behind big data.It is indispensable in the era of big data visualization,and it can be very intuitive if used properly.Graphical analysis also found that valuable information becomes a powerful tool in complex data relationships,and it represents a significant business opportunity.With the rise of big data,important technologies suitable for dealing with complex relationships have emerged.Graphics come in a variety of shapes and sizes for a variety of business problems.Graphic analysis is first in the visualization.The step is to get the right data and answer the goal.In short,to choose the right method,you must understand each relative strengths and weaknesses and understand the data.Key steps to get data:target;collect;clean;connect.
文摘Purpose: This paper explores a method of knowledge discovery by visualizing and analyzing co-occurrence relations among three or more entities in collections of journal articles.Design/methodology/approach: A variety of methods such as the model construction,system analysis and experiments are used. The author has improved Morris' crossmapping technique and developed a technique for directly describing,visualizing and analyzing co-occurrence relations among three or more entities in collections of journal articles.Findings: The visualization tools and the knowledge discovery method can efficiently reveal the multiple co-occurrence relations among three entities in collections of journal papers. It can reveal more and in-depth information than analyzing co-occurrence relations between two entities. Therefore,this method can be used for mapping knowledge domain that is manifested in association with the entities from multi-dimensional perspectives and in an all-round way.Research limitations: The technique could only be used to analyze co-occurrence relations of less than three entities at present.Practical implications: This research has expanded the study scope of co-occurrence analysis.The research result has provided a theoretical support for co-occurrence analysis.Originality/value: There has not been a systematic study on co-occurrence relations among multiple entities in collections of journal articles. This research defines multiple co-occurrence and the research scope,develops the visualization analysis tool and designs the analysis model of the knowledge discovery method.
文摘In recent years,the field of cold chain logistics for fruits and vegetables has emerged as a significant topic in academic research.This study adopts a bibliometric approach and utilizes the visual analysis tool CiteSpace to systematically investigate the progress of domestic research in this area.Based on 209 core articles retrieved from the CNKI(China National Knowledge Infrastructure)database from January 2007 to May 2024,the study constructs multi-dimensional knowledge graphs—including discipline co-occurrence networks,author collaboration networks,and keyword timezone maps.The analysis reveals several key findings:there is a marked upward trend in the annual number of publications,research hotspots have evolved in phases,and core research areas concentrate on the optimization of cold chain logistics systems,innovations in preservation technologies for fruits and vegetables,and the construction of agricultural product logistics networks.It is worth noting that quality control of fruits and vegetables,along with related technological challenges,may become prominent directions for future research.
文摘Purpose: The evolution of the socio-cognitive structure of the field of knowledge management(KM) during the period 1986–2015 is described. Design/methodology/approach: Records retrieved from Web of Science were submitted to author co-citation analysis(ACA) following a longitudinal perspective as of the following time slices: 1986–1996, 1997–2006, and 2007–2015. The top 10% of most cited first authors by sub-periods were mapped in bibliometric networks in order to interpret the communities formed and their relationships.Findings: KM is a homogeneous field as indicated by networks results. Nine classical authors are identified since they are highly co-cited in each sub-period, highlighting Ikujiro Nonaka as the most influential authors in the field. The most significant communities in KM are devoted to strategic management, KM foundations, organisational learning and behaviour, and organisational theories. Major trends in the evolution of the intellectual structure of KM evidence a technological influence in 1986–1996, a strategic influence in 1997–2006, and finally a sociological influence in 2007–2015.Research limitations: Describing a field from a single database can offer biases in terms of output coverage. Likewise, the conference proceedings and books were not used and the analysis was only based on first authors. However, the results obtained can be very useful to understand the evolution of KM research.Practical implications: These results might be useful for managers and academicians to understand the evolution of KM field and to(re)define research activities and organisational projects.Originality/value: The novelty of this paper lies in considering ACA as a bibliometric technique to study KM research. In addition, our investigation has a wider time coverage than earlier articles.
基金Supported by Philosophy and Social Science Foundation of Hunan Province,China,No.23YBJ08China Youth&Children Research Association,No.2023B01Research Project on the Theories and Practice of Hunan Women,No.22YB06.
文摘BACKGROUND In the rapidly evolving landscape of psychiatric research,2023 marked another year of significant progress globally,with the World Journal of Psychiatry(WJP)experiencing notable expansion and influence.AIM To conduct a comprehensive visualization and analysis of the articles published in the WJP throughout 2023.By delving into these publications,the aim is to deter-mine the valuable insights that can illuminate pathways for future research endeavors in the field of psychiatry.METHODS A selection process led to the inclusion of 107 papers from the WJP published in 2023,forming the dataset for the analysis.Employing advanced visualization techniques,this study mapped the knowledge domains represented in these papers.RESULTS The findings revealed a prevalent focus on key topics such as depression,mental health,anxiety,schizophrenia,and the impact of coronavirus disease 2019.Additionally,through keyword clustering,it became evident that these papers were predominantly focused on exploring mental health disorders,depression,anxiety,schizophrenia,and related factors.Noteworthy contributions hailed authors in regions such as China,the United Kingdom,United States,and Turkey.Particularly,the paper garnered the highest number of citations,while the American Psychiatric Association was the most cited reference.CONCLUSION It is recommended that the WJP continue in its efforts to enhance the quality of papers published in the field of psychiatry.Additionally,there is a pressing need to delve into the potential applications of digital interventions and artificial intelligence within the discipline.
文摘The development of the information age and globalization has challenged the training of technical talents in the 21st century, and the information media and technical skills are becoming increasingly important. As a creative sharing form of multimedia, the digital storytelling is being concerned by more and more educators because of its discipline applicability and media technology enhancing ability. In this study, the information visualization software, i.e. CiteSpace was applied to visualize and analyze the researches on digital storytelling from the aspects of key articles and citation hotspots, and make a review on the research status of the digital storytelling in the education fields, such as promoting language learning, and helping students develop the 21 st century skills.
文摘The aim of the paper is to identify and explore leading thematic areas within the research field related to Business Schools Accreditation in China.Based on data from the China National Knowledge Infrastructure(CNKI)database,the keywords frequency was analyzed,and the theory of mapping knowledge domain was used to visualize the keywords co-occurrence network to make further research of the heated issues.The findings indicate that the research scope involved in business school accreditation research is broad,and research content focus on teaching,management,talent cultivation.According to the results of keywords co-occurrence analysis of different stages,AACSB,AACSB Accreditation,international accreditation,business school,AOL,internationalization,accreditation are the most important issues to business school research in China,given their position and role in the research network.The paper generates the added value mainly from the point of view of theory development.
基金This work was supported by the Research Project of Postgraduate Education Reform in Harbin Institute of Technology,Research Project of Postgraduate Education and Teaching Reform in Harbin Institute of Technology(Weihai).
文摘The aim of the paper is to identify and explore leading development situation within the research field related to student classroom engagement.Using knowledge mapping tools,this paper conducted the visualization analysis on internationalliteraturein relation to student classroom engagementfrom the Web of Science databases.By combination of the statistical data and visualizationmapping,this paper studied on the research relationship networks and status for the co-authors'countries/institutions,co-citation documents/journalsand co-occurring keywordsbased on the sample datafromliterature.The results indicate that the number ofpublished papershasincreased obviously and expanded graduallysince 2000.Main countries and institutions of researches were the UnitedStates,Australia,United Kingdom,Canada and China in order,and these countries had intense collaboration.The theoretical basis of the research come from education and teaching,psychology.The hotspots of researches fromthe global literature coveredvarious fields including achievement,motivation,behavior,education,performance.As a result of the multidisciplinary integration,many relevant internationalresearch constantly expanded the research scopes,which promoted the combination and development of theories.
