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Готові списки джерел за темами / Knowledge based data management / Статті в журналах

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Статті в журналах з теми "Knowledge based data management"

Автор: Grafiati

Опубліковано: 20 квітня 2024

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1

Dettmar, Harvey, Xiaohui Liu, Roger Johnson, and Alan Payne. "Knowledge-based data generation." Knowledge-Based Systems 11, no. 3-4 (1998): 167–77. http://dx.doi.org/10.1016/s0950-7051(98)00031-8.

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2

Baoan, Li. "Knowledge Management Based on Big Data Processing." Information Technology Journal 13, no. 7 (2014): 1415–18. http://dx.doi.org/10.3923/itj.2014.1415.1418.

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3

Guo, Yu Dong. "Prototype System of Knowledge Management Based on Data Mining." Applied Mechanics and Materials 411-414 (September 2013): 251–54. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.251.

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Анотація:

Knowledge is a very crucial resource to promote economic development and society progress which includes facts, information, descriptions, or skills acquired through experience or education. With knowledge has being increasingly prominent, knowledge management has become important measure for the core competences promotion of a corporation. The paper begins with knowledge managements definition, and studies the process of knowledge discovery from databases (KDD),data mining techniques and SECI(Socialization, Externalization, Combination, Internalization) model of knowledge dimensions. Finally,

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4

Havlíček, J., J. Hron, and I. Tichá. "Knowledge based higher education." Agricultural Economics (Zemědělská ekonomika) 52, No. 3 (2012): 107–16. http://dx.doi.org/10.17221/5002-agricecon.

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While data and/or information based education was built on pedagogic, psychology, philosophy of science and didactic disciplines, the new dimension of knowledge based education will involve new disciplines such as Knowledge Management, Epistemology, Systems Theory, Artificial Knowledge Management Systems, Value Theory and Theory of Measurement. It is often assumed that data, information and knowledge are depicted as a pyramid. The data, the most plentiful type, are at the bottom, information, produced from data, is above it and knowledge, produced from information through the hard work of refi

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5

Asrin, Fauzan, *Saide Saide, and Silvia Ratna. "Data to Knowledge-Based Transformation." International Journal of Sociotechnology and Knowledge Development 13, no. 4 (2021): 141–52. http://dx.doi.org/10.4018/ijskd.2021100109.

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The objectives of this study is to analyze a large amount of data that often appears to create a knowledge base that can be utilized by firm to enhance their decision support system. The authors used the association rules with rapid miner software, data mining approach, and predictive analysis that contains various data exploration scenarios. The study provides important evidence for adopting data mining methods in the industrial sector and their advantages and disadvantages. Chevron Pacific Indonesia (CPI) has a type of computer maintenance activity. Currently, a numerous errors often occur d

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6

Šuman, Sabrina, Alen Jakupović, and Francesca Gržinić Kuljanac. "Knowledge-Based Systems for Data Modelling." International Journal of Enterprise Information Systems 12, no. 2 (2016): 1–13. http://dx.doi.org/10.4018/ijeis.2016040101.

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Data modelling is a complex process that depends on the knowledge and experience of the designers who carry it out. The quality of created models has a significant impact on the quality of successive phases of information systems development. This paper, in short, reviews the data modelling process, the entity-relationship method (ERM) and actors in the data modelling process. Further, in more detail it presents systems, methods, and tools for the data modelling process and identifies problems that occur during the development phase of an information system. These problems also represent the a

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7

BRADJI, Louardi, and Mahmoud BOUFAIDA. "A Rule Management System for Knowledge Based Data Cleaning." Intelligent Information Management 03, no. 06 (2011): 230–39. http://dx.doi.org/10.4236/iim.2011.36028.

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8

Radziszewska, Aleksandra. "Data-Driven Approach in Knowledge-Based Smart City Management." European Conference on Knowledge Management 24, no. 2 (2023): 1090–98. http://dx.doi.org/10.34190/eckm.24.2.1600.

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The concept of smart city management is based on the implementation and use of advanced technologies, such as wireless sensors, intelligent vehicles, mobile networks, and data storage technologies. It involves integrating various information and communication technology solutions to efficiently manage a city's resources. Cities are investing in data-driven smart technologies to enhance performance and efficiency, thereby generating a large amount of data. Finding innovative ways to use this data helps improve city management and urban development. A data-driven city utilizes datafication to op

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9

Boqing Feng, Boqing Feng, Xiaolei Xu Boqing Feng, Congxu Li Xiaolei Xu, Wenbin Liu Congxu Li, and Mohan Liu Wenbin Liu. "GIS-Based Electric Service Resource Management System." 電腦學刊 34, no. 3 (2023): 387–97. http://dx.doi.org/10.53106/199115992023063403029.

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<p>With the increasing investment in railway construction, China’s railway transport network is now very sound, the number of operating miles is growing, and the operating speed has also made a qualitative leap. At the same time, the safety and reliability of the operation of railway signal cables and other electrical equipment has also put forward higher requirements. At the present stage, the management of railway electrical services equipment mainly relies on manual management, which is cumbersome, inefficient and unsuitable for multi-user sharing. At the same time, the structure of r

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10

Sridhar, V., and M. Narasimha Murty. "Knowledge-based clustering approach for data abstraction." Knowledge-Based Systems 7, no. 2 (1994): 103–13. http://dx.doi.org/10.1016/0950-7051(94)90023-x.

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11

Janev, Valentina, Maria-Esther Vidal, Dea Pujić, et al. "Responsible Knowledge Management in Energy Data Ecosystems." Energies 15, no. 11 (2022): 3973. http://dx.doi.org/10.3390/en15113973.

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This paper analyzes the challenges and requirements of establishing energy data ecosystems (EDEs) as data-driven infrastructures that overcome the limitations of currently fragmented energy applications. It proposes a new data- and knowledge-driven approach for management and processing. This approach aims to extend the analytics services portfolio of various energy stakeholders and achieve two-way flows of electricity and information for optimized generation, distribution, and electricity consumption. The approach is based on semantic technologies to create knowledge-based systems that will a

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12

Kalaycı, Tahir Emre, Bor Bricelj, Marko Lah, Franz Pichler, Matthias K. Scharrer, and Jelena Rubeša-Zrim. "A Knowledge Graph-Based Data Integration Framework Applied to Battery Data Management." Sustainability 13, no. 3 (2021): 1583. http://dx.doi.org/10.3390/su13031583.

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Today, the automotive and transportation sector is undergoing a transformation process to meet the requirements of sustainable and efficient operations. This transformation mainly reveals itself by electric vehicles, hybrid electric vehicles, and electric vehicle sharing. One significant, and the most expensive, component in electric vehicles is the batteries, and the management of batteries is crucial. It is essential to perform constant monitoring of behavior changes for operational purposes and quickly adjust components and operations to these changes. Thus, to address these challenges, we

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13

Makani, Joyline. "Knowledge management, research data management, and university scholarship." VINE 45, no. 3 (2015): 344–59. http://dx.doi.org/10.1108/vine-07-2014-0047.

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Анотація:

Purpose – The purpose of this paper is to synthesize existing research on research data management (RDM), academic scholarship and knowledge management and provide a conceptual framework for an institutional research data management support-system (RDMSS) for systems development, managerial and academic use. Design/methodology/approach – Viewing RDMSS from multiple theoretical perspectives, including data management, knowledge management, academic scholarship and the practice-based perspectives of knowledge and knowing, this paper conceptually explores the systems’ elements needed in the devel

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14

Neumann, Michael. "Web-Based Data, Document, and Knowledge Management in Restoration Projects." Restoration Ecology 15, no. 2 (2007): 326–29. http://dx.doi.org/10.1111/j.1526-100x.2007.00218.x.

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15

Hogan, Michael F., and Susan M. Essock. "Data and decisions: Can mental health management be knowledge-based?" Journal of Mental Health Administration 18, no. 1 (1991): 12–20. http://dx.doi.org/10.1007/bf02521129.

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16

Console, Marco, and Maurizio Lenzerini. "Epistemic Integrity Constraints for Ontology-Based Data Management." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 03 (2020): 2790–97. http://dx.doi.org/10.1609/aaai.v34i03.5667.

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Ontology-based data management (OBDM) is a powerful knowledge-oriented paradigm for managing data spread over multiple heterogeneous sources. In OBDM, the data sources of an information system are handled through the reconciled view provided by an ontology, i.e., the conceptualization of the underlying domain of interest expressed in some formal language. In any information systems where the basic knowledge resides in data sources, it is of paramount importance to specify the acceptable states of such information. Usually, this is done via integrity constraints, i.e., requirements that the dat

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17

Nomura, Toshio, and Stephen Lunn. "Integration of knowledge-based systems with data processing." Knowledge-Based Systems 1, no. 1 (1987): 24–31. http://dx.doi.org/10.1016/0950-7051(87)90004-9.

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18

Huang, Li, Yongjun Han, Aihua Yuan, et al. "Performance Evaluation Method of Library Knowledge Management Based on Data Mining." Wireless Communications and Mobile Computing 2022 (June 21, 2022): 1–12. http://dx.doi.org/10.1155/2022/3358738.

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Анотація:

With the development of information technology and computer technology, the work of the library is becoming more and more digitized and networked. This article mainly studies the performance evaluation method of library knowledge management based on data mining. This paper uses attribute-oriented induction algorithm to mine generalized features. First, scan the entire data set to obtain different values of all attributes. Statistics, classification, and analysis of historical records help to understand the usage of books and periodicals and perform predictive analysis. This article uses statis

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19

Smith, Alan D., and William T. Rupp. "Data Quality and Knowledge/Information Management in Service Operations Management." International Journal of Knowledge-Based Organizations 3, no. 3 (2013): 35–52. http://dx.doi.org/10.4018/ijkbo.2013070103.

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The concepts of managing data quality assurance by promoting proper safeguards to manage data quality, employee buy-in, and support from top management were illustrated in a case study of Giant Eagle, one of the largest, privately owned and family-operated companies in the U.S. and regional headquartered in Pittsburgh, PA. Specific aspects of data quality assurance, types of access, application examples (especially with its loyalty-card collection and data-mining uses that allow customers to accumulate savings specials and rewards through the fuelperks!™ and foodperks!™ incentive programs), as

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20

Raja, K., and S. K. Srivatsa . "A Distributed Data Management in Knowledge Based Group Decision Support Systems." Journal of Applied Sciences 6, no. 1 (2005): 27–30. http://dx.doi.org/10.3923/jas.2006.27.30.

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21

Rodríguez-Enríquez, Cristian Aarón, Giner Alor-Hernández, Cuauhtémoc Sánchez-Ramírez, and Guillermo Córtes-Robles. "Supply chain knowledge management: A linked data-based approach using SKOS." DYNA 82, no. 194 (2015): 27–35. http://dx.doi.org/10.15446/dyna.v82n194.54463.

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22

Yoo, Sang Bong, and Yeongho Kim. "Web-based knowledge management for sharing product data in virtual enterprises." International Journal of Production Economics 75, no. 1-2 (2002): 173–83. http://dx.doi.org/10.1016/s0925-5273(01)00190-6.

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23

García-Saiz, Diego, Marta Zorrilla, and José Luis Bosque. "A clustering-based knowledge discovery process for data centre infrastructure management." Journal of Supercomputing 73, no. 1 (2016): 215–26. http://dx.doi.org/10.1007/s11227-016-1693-z.

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24

Li, Yan, Manoj A. Thomas, and Kweku-Muata Osei-Bryson. "Ontology-based data mining model management for self-service knowledge discovery." Information Systems Frontiers 19, no. 4 (2016): 925–43. http://dx.doi.org/10.1007/s10796-016-9637-y.

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25

Zeleny, Milan. "Integrated Knowledge Management." International Journal of Information Systems and Social Change 4, no. 4 (2013): 62–78. http://dx.doi.org/10.4018/jissc.2013100104.

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Анотація:

In this paper the author presents the inception of Integrated Knowledge Management (IKM). Knowledge management is entering its new stage, after the delays of its “definitionless”, IT-based period, when knowledge got confused with information, losing thus two decades of fruitful development. Although there now is a significant information overload, killing productivity, creativity and innovation, there can never be any knowledge overload. Knowledge is fundamentally different from information. The integration of data, information, knowledge and wisdom into a coherent and unified management suppo

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26

Ramazanov, E. T., S. E. Sibanbaeva, and N. V. Koroleva. "Development of local knowledge cube of knowledge management system." Bulletin of the National Engineering Academy of the Republic of Kazakhstan 91, no. 1 (2024): 103–10. http://dx.doi.org/10.47533/2024.1606-146x.11.

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The article presents the results of a study on the development of a knowledge management system in an enterprise based on the concept of knowledge management. Considered guesses on the functional scheme in the concept of the system. A scheme of the system is proposed by analogy with a local OLAP cube. A heuristic algorithm for detecting knowledge in data is constructed. A heuristic algorithm for detecting knowledge in data is constructed. A mathematical description of the algorithm based on the methods of first-order logic, the production model of knowledge representation and methods of knowle

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27

Fitzsimmons, Sharon. "Preventing MBSE Amnesia through Role‐Based Knowledge Management." INCOSE International Symposium 33, no. 1 (2023): 183–96. http://dx.doi.org/10.1002/iis2.13016.

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AbstractThe problems of knowledge management (KM) have changed in the last thirty years since its introduction, as evidenced by the decrease in searches for “knowledge management” and the up‐tick in Google trends for searches on “big data.” With the introduction of Web 2.0, the amount of data available within a company has exploded, but a company's technology for navigating that data has not necessarily kept up. Consequently, companies are at high risk for organizational knowledge loss. This is particularly acute in new technologies that suffer from a labor shortage, such as Model‐Based System

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28

Wu, Ing-Long, and Ya-Ping Hu. "Open innovation based knowledge management implementation: a mediating role of knowledge management design." Journal of Knowledge Management 22, no. 8 (2018): 1736–56. http://dx.doi.org/10.1108/jkm-06-2016-0238.

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Purpose Knowledge-based organizations is a new paradigm for business. Knowledge management (KM) is important for supporting core business processes. This paper aims to define an open innovation (OI)-driven KM implementation for effectively executing the support. Design/methodology/approach KM is important for supporting organizational innovation. OI plays a critical determinant role in defining the design of KM for effectively supporting OI. Further, the final goal of KM is to reach the success of OI-based KM implementation. A model is thus proposed for connecting OI as a driver to a design of

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29

Luo, Ya Ling, Shi Qiang Zhang, Su Xin Wan, and Tian Jing Zhou. "A Study of Knowledge Management System Based on Data Resources of Medical Industry." Applied Mechanics and Materials 651-653 (September 2014): 1784–89. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.1784.

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The modern hospital is a knowledge intensity organization and the knowledge management has become inevitable development trend of the hospital management. The medical profession background is the data resources of the health profession, and the quality of data resources directly influences the effect of hospital knowledge management. How to fully use the data resources of hospital for enhancing the innovation strength and the core competitive power of the hospital have already become the main focus of the health and academic professionals. The current status of medical profession data resource

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30

Alijanzadeh, Ebrahim, Ali Asghar Razavi, and Safiyeh T. Ahmasebi Limuni. "Predicting Job Performance Based on Knowledge Management." Journal of Management and Accounting Studies 8, no. 4 (2020): 34–38. http://dx.doi.org/10.24200/jmas.vol8iss4pp34-38.

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The objective of this research is to predict job performance based on knowledge management. The methodology of this research was applied according to its objective and descriptive-correlational based on the execution method. The statistical population of this research is all the librarians from public libraries of Mazandaran province with 265 members by full-census manner. 179 questionnaires were turned back. The research tool was Hosseinzadeh (2019) personal knowledge management questionnaire and Hosseini job performance questionnaire (2013). Cronbach’s alpha coefficient was used to estimate

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31

Wang, Hao, and Xianhai Meng. "BIM-Based Knowledge Management in Construction Projects." International Journal of Information Technology Project Management 9, no. 2 (2018): 20–37. http://dx.doi.org/10.4018/ijitpm.2018040102.

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Construction organizations have increasingly realized the importance of knowledge management (KM). They have also increasingly applied various tools and strategies to manage their knowledge. Due to the temporary nature of construction projects, however, there continues to be certain barriers and challenges of KM that are hard to overcome. This article explores the use of Building Information Modelling (BIM) to achieve better KM in UK construction organizations. First of all, why and how BIM can facilitate KM in construction projects are identified from the literature review. Secondly, a questi

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32

Huang, Zhaoyan, and Tao Xu. "Research on Knowledge Management of Intangible Cultural Heritage Based on Linked Data." Mobile Information Systems 2022 (August 27, 2022): 1–14. http://dx.doi.org/10.1155/2022/3384391.

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At present, the protection of intangible cultural heritage has received more and more attention from all levels of society. Intangible cultural heritage is a treasure of national culture. It is an indispensable part of Chinese civilization, the crystallization of the wisdom of Chinese civilization, and represents the country’s soft power. The effective organization and management of intangible cultural heritage knowledge is the premise and foundation for the protection, dissemination, and inheritance of intangible cultural heritage. Ontology and linked data technology provide a new method and

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33

Kirschfink, Heribert. "Knowledge-based system for the completion of traffic data." European Journal of Operational Research 71, no. 2 (1993): 247–56. http://dx.doi.org/10.1016/0377-2217(93)90052-o.

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34

Ngah, Rohana, and Kuan Yew Wong. "Linking knowledge management to competitive strategies of knowledge-based SMEs." Bottom Line 33, no. 1 (2020): 42–59. http://dx.doi.org/10.1108/bl-08-2019-0105.

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Purpose This paper aims to study the effect of knowledge management in formulating competitive strategies for knowledge-based small- and medium-sized enterprises (SMEs) in Malaysia. Design/methodology/approach A quantitative approach of a survey was carried out on 135 owners and managers of knowledge-based SMEs in Malaysia. Structural equation modeling technique was used to investigate the relationship between knowledge management and competitive strategies. SmartPLS software is used to analyze the quantitative data. Only SMEs which are involved in R&D and innovation were selected to get t

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35

Hadj Sassi, Mohamed Saifeddine, Lamia Chaari Fourati, Manel Zekri, and Sadok Ben Yahia. "Knowledge Management Process for Air Quality Systems based on Data Warehouse Specification." Procedia Computer Science 192 (2021): 29–38. http://dx.doi.org/10.1016/j.procs.2021.08.004.

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36

Heinrichs, John H., and Jeen-Su Lim. "Integrating web-based data mining tools with business models for knowledge management." Decision Support Systems 35, no. 1 (2003): 103–12. http://dx.doi.org/10.1016/s0167-9236(02)00098-2.

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37

Mouton, A. M., B. De Baets, and P. L. M. Goethals. "Knowledge-based versus data-driven fuzzy habitat suitability models for river management." Environmental Modelling & Software 24, no. 8 (2009): 982–93. http://dx.doi.org/10.1016/j.envsoft.2009.02.005.

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38

Albert, T. M. "Knowledge-based geographic information systems (KBGIS): New analytic and data management tools." Mathematical Geology 20, no. 8 (1988): 1021–35. http://dx.doi.org/10.1007/bf00892977.

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39

Goodman, A. M., R. M. Haralick, and L. G. Shapiro. "Knowledge-based computer vision-integrated programming language and data management system design." Computer 22, no. 12 (1989): 43–54. http://dx.doi.org/10.1109/2.42031.

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40

Walsh, John N., and Jamie O’Brien. "A Knowledge-Based Framework for Service Management." Journal of Information & Knowledge Management 16, no. 04 (2017): 1750039. http://dx.doi.org/10.1142/s0219649217500393.

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Анотація:

The purpose of this paper is to investigate how information and communication technologies are used for service standardisation, customisation, and modularisation by knowledge-intensive service firms through the development and empirical validation of a knowledge-based framework. This paper uses 59 in-depth interviews, observational data, and document analysis from case studies of three service-related departments in high-technology, multinational knowledge-intensive business services (KIBSs). Prior research does not conceptualise the relationships between service customisation, standardisatio

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41

Kurniawan, Yohannes. "Knowledge Management for Manufacturing Process Based on Knowledge Lifecycle to Enhance Data Sharing (Perception: Application and Benefits)." Applied Mechanics and Materials 391 (September 2013): 366–71. http://dx.doi.org/10.4028/www.scientific.net/amm.391.366.

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Анотація:

The importance of effective knowledge management is well recognized in a number of manufacturing companies. There is still, however, a clear need to further reinforce applications of knowledge management tools by effectively solving fundamental and specific problems related to knowledge management practice in manufacturing industry. The paper presents the concept specifically for the business case at the palm oil companies, where the tools are used to transfer the knowledge over different life cycles of the production process to enhance data sharing. This paper put forward a knowledge manageme

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42

Gulnoza, Rakhimova. "Analyzing the Impact of Distributed Data and Knowledge-Based Systems on Knowledge Management: A Systematic Mapping Study." International Journal of Advances in Applied Computational Intelligence 4, no. 2 (2023): 41–47. http://dx.doi.org/10.54216/ijaaci.040205.

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Анотація:

Knowledge management is a critical aspect of modern organizations seeking to harness their collective intelligence and remain competitive in a dynamic business environment. With the advent of distributed data and knowledge-based systems, the landscape of knowledge management is undergoing significant transformations. This systematic mapping study aims to provide a comprehensive overview of the current state of knowledge management within the context of distributed environments and knowledge-based systems, shedding light on the key trends and challenges that shape this evolving field. Our study

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43

Koltay, Tibor. "Data governance, data literacy and the management of data quality." IFLA Journal 42, no. 4 (2016): 303–12. http://dx.doi.org/10.1177/0340035216672238.

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Data governance and data literacy are two important building blocks in the knowledge base of information professionals involved in supporting data-intensive research, and both address data quality and research data management. Applying data governance to research data management processes and data literacy education helps in delineating decision domains and defining accountability for decision making. Adopting data governance is advantageous, because it is a service based on standardised, repeatable processes and is designed to enable the transparency of data-related processes and cost reducti

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44

Zhai, Jun, Jian Feng Li, and Yan Chen. "Knowledge Modeling of Product Data Based on Fuzzy Ontology." Applied Mechanics and Materials 26-28 (June 2010): 347–51. http://dx.doi.org/10.4028/www.scientific.net/amm.26-28.347.

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Анотація:

Ontology is the basis of knowledge modeling on the Semantic Web, and fuzzy ontology is an extension of domain ontology for solving the uncertainty problems. Ontology-base knowledge modeling of product data management (PDM) is meaningful for product design and trade etc. In order to handle fuzzy phenomenon and uncertainty of product knowledge, this paper proposes a series of fuzzy ontology models that consists of fuzzy domain ontology and fuzzy linguistic variable ontologies. Then, a fuzzy ontology framework is presented, including three parts: concepts, properties of concepts and values of pro

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R. Dhaya, R. Dhaya, R. Kanthavel R. Dhaya, and Kanagaraj Venusamy R. Kanthavel. "AI Based Learning Model Management Framework for Private Cloud Computing." 網際網路技術學刊 23, no. 7 (2022): 1633–42. http://dx.doi.org/10.53106/160792642022122307017.

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<p>Artificial Intelligence (AI) systems are computational simulations that are &ldquo;educated&rdquo; using knowledge and individual expert participation to replicate a decision that a professional would make provided the same data. A model tries to simulate a specific decision loop that several scientists would take if they had access to all kinds of knowledge. To convey a model, you make a model asset in AI Platform Prediction, make a variant of that model and, at that point, interface the model form to the model record put away in Cloud Storage. AI and DB information sharing a

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Sousa, Cristóvão, Daniel Teixeira, Davide Carneiro, Diogo Nunes, and Paulo Novais. "Knowledge-based decision intelligence in street lighting management." Integrated Computer-Aided Engineering 29, no. 2 (2022): 189–207. http://dx.doi.org/10.3233/ica-210671.

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As the availability of computational power and communication technologies increases, Humans and systems are able to tackle increasingly challenging decision problems. Taking decisions over incomplete visions of a situation is particularly challenging and calls for a set of intertwined skills that must be put into place under a clear rationale. This work addresses how to deliver autonomous decisions for the management of a public street lighting network, to optimize energy consumption without compromising light quality patterns. Our approach is grounded in an holistic methodology, combining sem

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Böckenholt, I., M. Both, and W. Gaul. "A knowledge-based system for supporting data analysis problems." Decision Support Systems 5, no. 4 (1989): 345–54. http://dx.doi.org/10.1016/0167-9236(89)90014-6.

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Freeze, Ronald D., and Uday Kulkarni. "Knowledge management capability: defining knowledge assets." Journal of Knowledge Management 11, no. 6 (2007): 94–109. http://dx.doi.org/10.1108/13673270710832190.

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PurposeThe purpose of this paper is to show that separate sources of knowledge are identified, described and clearly defined as organizational intangible knowledge assets. These knowledge assets are referred to as knowledge capabilities (KCs). knowledge management (KM) is utilized to leverage these assets with a view to systematic improvement in the process of achieving increased firm performance.Design/methodology/approachIn this paper knowledge capabilities are described in terms of their knowledge life cycle, tacit/implicit/explicit nature of knowledge, technology and organizational process

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Alryalat, Haroun, and Samer Al Hawari. "Towards Customer Knowledge Relationship Management: Integrating Knowledge Management and Customer Relationship Management Process." Journal of Information & Knowledge Management 07, no. 03 (2008): 145–57. http://dx.doi.org/10.1142/s0219649208002020.

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Due to the strong competition that exists among organisations and the rapid change in the business environment, knowledge has turned out to become a key source for organisations to enhance the competitive advantage. Integrating Knowledge Management (KM) and Customer Relationship Management (CRM) process is a new research area, therefore, scientific research and literature around it remain limited. In addition, the impact of KM process on customer acquisition, retention, and expansion to improve customer satisfaction remains under study and report. The aim of this paper is to present a conceptu

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Macbeth, Sam, and Jeremy V. Pitt. "Self-organising management of user-generated data and knowledge." Knowledge Engineering Review 30, no. 3 (2014): 237–64. http://dx.doi.org/10.1017/s026988891400023x.

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AbstractThe proliferation of sensor networks, mobile and pervasive computing has provided the technological push for a new class of participatory-sensing applications, based on sensing and aggregating user-generated content, and transforming it into knowledge. However, given the power and value of both the raw data and the derived knowledge, to ensure that the generators are commensurate beneficiaries, we advocate an open approach to the data and intellectual property rights by treating user-generated content, as well as derived information and knowledge, as a common-pool resource. In this pap

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