This paper is based on two existing theories about automatic indexing of thematic knowledge concept. The prohibit-word table with position information has been designed. The improved Maximum Matching-Minimum Backtrack...This paper is based on two existing theories about automatic indexing of thematic knowledge concept. The prohibit-word table with position information has been designed. The improved Maximum Matching-Minimum Backtracking method has been researched. Moreover it has been studied on improved indexing algorithm and application technology based on rules and thematic concept word table.展开更多
The acquisition of word knowledge, in terms of breadth and depth, has a fundamental impact on language learning. A comprehensive framework of word knowledge is therefore needed to help language learners master all the...The acquisition of word knowledge, in terms of breadth and depth, has a fundamental impact on language learning. A comprehensive framework of word knowledge is therefore needed to help language learners master all the aspects of word knowledge. This paper proposed a framework of word knowledge based on the literature review of the field. The pedagogical implications of the word knowledge framework were then proposed and discussed critically. Finally, it is proposed that syllabus designers need to consider the possibility of incorporating ＂word knowledge framework＂ into syllabus.展开更多
COMPUTATIONAL knowledge vision[1]is emphasized as a novel perspective or field in this paper.It first proposes the visual hierarchy and its connection to knowledge,stating that knowledge is a justified true belief.To ...COMPUTATIONAL knowledge vision[1]is emphasized as a novel perspective or field in this paper.It first proposes the visual hierarchy and its connection to knowledge,stating that knowledge is a justified true belief.To further the previous research,we concisely summarize our recent works and suggest a new direction that knowledge is also a thought framework in vision.展开更多
With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. Fir...With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. First, some valid mining task schedules are generated, and then au tonomous and local mining are executed periodically, finally, previous results are merged and refined. The framework based on the model creates a communication mechanism to in corporate domain knowledge into continuous process through ontology service. The local and merge mining are transparent to the end user and heterogeneous data ,source by ontology. Experiments suggest that the framework should be useful in guiding the continuous mining process.展开更多
The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge ...The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge management- the knowledge domain framework （KDF）, and introduces an integrated development environment （IDE） named large-scale ontology development environment （LODE）, which implements the proposed theoretical framework. We also compared LODE with other popular ontology development environments in this paper. The practice of using LODE on management and development of agriculture ontologies shows that knowledge domain framework can handle the development activities of large scale ontologies. Application studies based on the described briefly. principle of knowledge domain framework and LODE was展开更多
This study aims at developing a Knowledge Management Implementation Framework for adoption by firms in the Ghanaian construction industry. Recent developments in the field of Knowledge management in the construction s...This study aims at developing a Knowledge Management Implementation Framework for adoption by firms in the Ghanaian construction industry. Recent developments in the field of Knowledge management in the construction sector have led to a renewed competition in driving organizational performance. However, the construction industry in Ghana lacks a knowledge management implementation framework that addresses the needs of the Ghanaian construction supply chain while a comprehensive approach to managing knowledge remains nebulous. The study adopted an extensive literature review of existing knowledge management models to provide the basis for the development of the proposed framework for Ghana. The proposed knowledge management implementation framework was subjected to testing and validation by project managers drawn from nineteen indigenous construction firms in Ghana. The technology acceptance model (TAM) was used as the criteria to validate the proposed knowledge management implementation framework. The proposed Guribie & Tengan knowledge management implementation framework was perceived to be useful, and easy to use and the intention to adopt and use was high among indigenous Ghanaian construction firms. The study recommends further validation using wider population to enhance the efficacy of the framework for wider industry acceptance to enhance organizational competitiveness and performance delivery.展开更多
Time is an essential reference system for recording objects,events,and processes in the field of geosciences.There are currently various time references,such as solar calendar,geological time,and regional calendar,to ...Time is an essential reference system for recording objects,events,and processes in the field of geosciences.There are currently various time references,such as solar calendar,geological time,and regional calendar,to represent the knowledge in different domains and regions,which subsequently entails a time conversion process required to interpret temporal information under different time references.However,the current time conversion method is limited by the application scope of existing time ontologies(e.g.,“Jurassic”is a period in geological ontology,but a point value in calendar ontology)and the reliance on experience in conversion processes.These issues restrict accurate and efficient calculation of temporal information across different time references.To address these issues,this paper proposes a Unified Time Framework(UTF)in the geosciences knowledge system.According to a systematic time element parsing from massive time references,the proposed UTF designs an independent time root node to get rid of irrelevant nodes when accessing different time types and to adapt to the time expression of different geoscience disciplines.Furthermore,this UTF carries out several designs:to ensure the accuracy of time expressions by designing quantitative relationship definitions;to enable time calculations across different time elements by designing unified time nodes and structures,and to link to the required external ontologies by designing adequate interfaces.By comparing the time conversion methods,the experiment proves the UTF greatly supports accurate and efficient calculation of temporal information across different time references in SPARQL queries.Moreover,it shows a higher and more stable performance of temporal information queries than the time conversion method.With the advent of the Big Data era in the geosciences,the UTF can be used more widely to discover new geosciences knowledge across different time references.展开更多
Knowledge Management(KM)has become a dynamic concept for inquiry in research.The management of knowledge from multiple sources requires a systematic approach that can facilitate capturing all important aspects related...Knowledge Management(KM)has become a dynamic concept for inquiry in research.The management of knowledge from multiple sources requires a systematic approach that can facilitate capturing all important aspects related to a particular discipline,several KM frameworks have been designed to serve this purpose.This research aims to propose a Collaborative Knowledge Management(CKM)Framework that bridges gaps and overcomes weaknesses in existing frameworks.The paper also validates the framework by evaluating its effectiveness for the agriculture sector of Pakistan.A software LCWU aKMS was developed which serves as a practical implementation of the concepts behind the proposed CKMF framework.LCWU aKMS served as an effective system for rice leaf disease detection and identification.It aimed to enhance CKM through knowledge sharing,lessons learned,feedback on problem resolutions,help from co-workers,collaboration,and helping communities.Data were collected from 300 rice crop farmers by questionnaires based on hypotheses.Jennex Olfman model was used to estimate the effectiveness of CKMF.Various tests were performed including frequency measures of variables,Cronbach’s alpha reliability,and Pearson’s correlation.The research provided a KMS depicting KM and collaborative features.The disease detection module was evaluated using the precision and recall method and found to be 94.16%accurate.The system could replace the work of extension agents,making it a cost and time-effective initiative for farmer betterment.展开更多
In complicated application environment such as CIMS (Computer Integrated Manufacture System) enterprise, it will bring great benefits to integrate distributed knowledge sources. But the difficulties of knowledge shari...In complicated application environment such as CIMS (Computer Integrated Manufacture System) enterprise, it will bring great benefits to integrate distributed knowledge sources. But the difficulties of knowledge sharing and reuse seriously encumbrance the implementation of knowledge integration. In this paper, we describe how a framework of knowledge-integrated system based on ontology (KISO) can be used to support integrating distributed knowledge sources.展开更多
Many studies have shown that knowledge resources have been the real source of innovation and competitiveness of real estate enterprises. Therefore, it is the basic work to establish the real estate enterprise knowledg...Many studies have shown that knowledge resources have been the real source of innovation and competitiveness of real estate enterprises. Therefore, it is the basic work to establish the real estate enterprise knowledge resources framework for implementing knowledge management（KM）,and it should be given enough attention. A sort of the real estate enterprise knowledge resources framework system has been built in this paper based on the thought of Clark ＆ Henderson＇s enterprise knowledge classification, and the contents have been analyzed and expounded. Thus, the real estate enterprises can grasp clearly the basic contents of its knowledge resources, then depict the knowledge system, in the end the solid foundation should be settled for implementing knowledge management.展开更多
The evolution of the society and economy has stimulated the development of Knowledge Service(KS), making it an indispensable solution to address future challenges facing libraries and information institutions. However...The evolution of the society and economy has stimulated the development of Knowledge Service(KS), making it an indispensable solution to address future challenges facing libraries and information institutions. However at present, academic research on knowledge service is falling short and its definition is far from clear and complete. As such,this article proposes the Three-dimensional Framework Knowledge Service(TdFKS) for libraries and information institutions based on the knowledge value chain model. By making reliability analysis and mean value analysis of a questionnaire survey result, the article clarifies the structure of the three-dimensional framework and verifies the rationality of the TdFKS.展开更多
Knowledge distillation(KD) enhances student network generalization by transferring dark knowledge from a complex teacher network. To optimize computational expenditure and memory utilization, self-knowledge distillati...Knowledge distillation(KD) enhances student network generalization by transferring dark knowledge from a complex teacher network. To optimize computational expenditure and memory utilization, self-knowledge distillation(SKD) extracts dark knowledge from the model itself rather than an external teacher network. However, previous SKD methods performed distillation indiscriminately on full datasets, overlooking the analysis of representative samples. In this work, we present a novel two-stage approach to providing targeted knowledge on specific samples, named two-stage approach self-knowledge distillation(TOAST). We first soften the hard targets using class medoids generated based on logit vectors per class. Then, we iteratively distill the under-trained data with past predictions of half the batch size. The two-stage knowledge is linearly combined, efficiently enhancing model performance. Extensive experiments conducted on five backbone architectures show our method is model-agnostic and achieves the best generalization performance.Besides, TOAST is strongly compatible with existing augmentation-based regularization methods. Our method also obtains a speedup of up to 2.95x compared with a recent state-of-the-art method.展开更多
基金the Science Foundation of Shanghai Archive Bureau (0215)
文摘This paper is based on two existing theories about automatic indexing of thematic knowledge concept. The prohibit-word table with position information has been designed. The improved Maximum Matching-Minimum Backtracking method has been researched. Moreover it has been studied on improved indexing algorithm and application technology based on rules and thematic concept word table.
文摘The acquisition of word knowledge, in terms of breadth and depth, has a fundamental impact on language learning. A comprehensive framework of word knowledge is therefore needed to help language learners master all the aspects of word knowledge. This paper proposed a framework of word knowledge based on the literature review of the field. The pedagogical implications of the word knowledge framework were then proposed and discussed critically. Finally, it is proposed that syllabus designers need to consider the possibility of incorporating ＂word knowledge framework＂ into syllabus.
基金supported in part by the Natural Science Foundation of China(62303361)in part by the Hainan Provincial Natural Science Foundation of China(623QN266)+2 种基金the Fundamental Research Funds for the Central Universities(WUT:233110002)in part by the University-Industry Collaborative Education Program(231002531131826)in part by the National Key R&D Program of China(2018AAA0101502)
文摘COMPUTATIONAL knowledge vision[1]is emphasized as a novel perspective or field in this paper.It first proposes the visual hierarchy and its connection to knowledge,stating that knowledge is a justified true belief.To further the previous research,we concisely summarize our recent works and suggest a new direction that knowledge is also a thought framework in vision.
基金Supported by the National Natural Science Foun-dation of China (60173058 ,70372024)
文摘With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. First, some valid mining task schedules are generated, and then au tonomous and local mining are executed periodically, finally, previous results are merged and refined. The framework based on the model creates a communication mechanism to in corporate domain knowledge into continuous process through ontology service. The local and merge mining are transparent to the end user and heterogeneous data ,source by ontology. Experiments suggest that the framework should be useful in guiding the continuous mining process.
基金supported by the Key Technology R&D Program of China during the 12th Five-Year Plan period:Super-Class Scientific and Technical Thesaurus and Ontology Construction Faced the Foreign Scientific and Technical Literature (2011BAH10B01)
文摘The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge management- the knowledge domain framework （KDF）, and introduces an integrated development environment （IDE） named large-scale ontology development environment （LODE）, which implements the proposed theoretical framework. We also compared LODE with other popular ontology development environments in this paper. The practice of using LODE on management and development of agriculture ontologies shows that knowledge domain framework can handle the development activities of large scale ontologies. Application studies based on the described briefly. principle of knowledge domain framework and LODE was
文摘This study aims at developing a Knowledge Management Implementation Framework for adoption by firms in the Ghanaian construction industry. Recent developments in the field of Knowledge management in the construction sector have led to a renewed competition in driving organizational performance. However, the construction industry in Ghana lacks a knowledge management implementation framework that addresses the needs of the Ghanaian construction supply chain while a comprehensive approach to managing knowledge remains nebulous. The study adopted an extensive literature review of existing knowledge management models to provide the basis for the development of the proposed framework for Ghana. The proposed knowledge management implementation framework was subjected to testing and validation by project managers drawn from nineteen indigenous construction firms in Ghana. The technology acceptance model (TAM) was used as the criteria to validate the proposed knowledge management implementation framework. The proposed Guribie & Tengan knowledge management implementation framework was perceived to be useful, and easy to use and the intention to adopt and use was high among indigenous Ghanaian construction firms. The study recommends further validation using wider population to enhance the efficacy of the framework for wider industry acceptance to enhance organizational competitiveness and performance delivery.
基金funded by the National Natural Science Foundation of China(Grant Nos.42050101 and 42101467)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA23100101).
文摘Time is an essential reference system for recording objects,events,and processes in the field of geosciences.There are currently various time references,such as solar calendar,geological time,and regional calendar,to represent the knowledge in different domains and regions,which subsequently entails a time conversion process required to interpret temporal information under different time references.However,the current time conversion method is limited by the application scope of existing time ontologies(e.g.,“Jurassic”is a period in geological ontology,but a point value in calendar ontology)and the reliance on experience in conversion processes.These issues restrict accurate and efficient calculation of temporal information across different time references.To address these issues,this paper proposes a Unified Time Framework(UTF)in the geosciences knowledge system.According to a systematic time element parsing from massive time references,the proposed UTF designs an independent time root node to get rid of irrelevant nodes when accessing different time types and to adapt to the time expression of different geoscience disciplines.Furthermore,this UTF carries out several designs:to ensure the accuracy of time expressions by designing quantitative relationship definitions;to enable time calculations across different time elements by designing unified time nodes and structures,and to link to the required external ontologies by designing adequate interfaces.By comparing the time conversion methods,the experiment proves the UTF greatly supports accurate and efficient calculation of temporal information across different time references in SPARQL queries.Moreover,it shows a higher and more stable performance of temporal information queries than the time conversion method.With the advent of the Big Data era in the geosciences,the UTF can be used more widely to discover new geosciences knowledge across different time references.
文摘Knowledge Management(KM)has become a dynamic concept for inquiry in research.The management of knowledge from multiple sources requires a systematic approach that can facilitate capturing all important aspects related to a particular discipline,several KM frameworks have been designed to serve this purpose.This research aims to propose a Collaborative Knowledge Management(CKM)Framework that bridges gaps and overcomes weaknesses in existing frameworks.The paper also validates the framework by evaluating its effectiveness for the agriculture sector of Pakistan.A software LCWU aKMS was developed which serves as a practical implementation of the concepts behind the proposed CKMF framework.LCWU aKMS served as an effective system for rice leaf disease detection and identification.It aimed to enhance CKM through knowledge sharing,lessons learned,feedback on problem resolutions,help from co-workers,collaboration,and helping communities.Data were collected from 300 rice crop farmers by questionnaires based on hypotheses.Jennex Olfman model was used to estimate the effectiveness of CKMF.Various tests were performed including frequency measures of variables,Cronbach’s alpha reliability,and Pearson’s correlation.The research provided a KMS depicting KM and collaborative features.The disease detection module was evaluated using the precision and recall method and found to be 94.16%accurate.The system could replace the work of extension agents,making it a cost and time-effective initiative for farmer betterment.
文摘In complicated application environment such as CIMS (Computer Integrated Manufacture System) enterprise, it will bring great benefits to integrate distributed knowledge sources. But the difficulties of knowledge sharing and reuse seriously encumbrance the implementation of knowledge integration. In this paper, we describe how a framework of knowledge-integrated system based on ontology (KISO) can be used to support integrating distributed knowledge sources.
基金Jiangsu Planned Projects for Postdoctoral Research Funds(No.0802076C)
文摘Many studies have shown that knowledge resources have been the real source of innovation and competitiveness of real estate enterprises. Therefore, it is the basic work to establish the real estate enterprise knowledge resources framework for implementing knowledge management（KM）,and it should be given enough attention. A sort of the real estate enterprise knowledge resources framework system has been built in this paper based on the thought of Clark ＆ Henderson＇s enterprise knowledge classification, and the contents have been analyzed and expounded. Thus, the real estate enterprises can grasp clearly the basic contents of its knowledge resources, then depict the knowledge system, in the end the solid foundation should be settled for implementing knowledge management.
基金supported by the National Planning Office of Philosophy and Social Science(Grant No.06BTQ027)
文摘The evolution of the society and economy has stimulated the development of Knowledge Service(KS), making it an indispensable solution to address future challenges facing libraries and information institutions. However at present, academic research on knowledge service is falling short and its definition is far from clear and complete. As such,this article proposes the Three-dimensional Framework Knowledge Service(TdFKS) for libraries and information institutions based on the knowledge value chain model. By making reliability analysis and mean value analysis of a questionnaire survey result, the article clarifies the structure of the three-dimensional framework and verifies the rationality of the TdFKS.
基金supported by the National Natural Science Foundation of China (62176061)。
文摘Knowledge distillation(KD) enhances student network generalization by transferring dark knowledge from a complex teacher network. To optimize computational expenditure and memory utilization, self-knowledge distillation(SKD) extracts dark knowledge from the model itself rather than an external teacher network. However, previous SKD methods performed distillation indiscriminately on full datasets, overlooking the analysis of representative samples. In this work, we present a novel two-stage approach to providing targeted knowledge on specific samples, named two-stage approach self-knowledge distillation(TOAST). We first soften the hard targets using class medoids generated based on logit vectors per class. Then, we iteratively distill the under-trained data with past predictions of half the batch size. The two-stage knowledge is linearly combined, efficiently enhancing model performance. Extensive experiments conducted on five backbone architectures show our method is model-agnostic and achieves the best generalization performance.Besides, TOAST is strongly compatible with existing augmentation-based regularization methods. Our method also obtains a speedup of up to 2.95x compared with a recent state-of-the-art method.
