Relevant bibliographies by topics / Knowledge based sysems

Academic literature on the topic 'Knowledge based sysems'

Author: Grafiati
Published: 10 December 2022
Last updated: 19 February 2023

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Journal articles on the topic "Knowledge based sysems"

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Loudon, T. Victor. "Wissensbasierte Systeme und geologische Feldaufnahme." Zeitschrift der Deutschen Geologischen Gesellschaft 155, no. 2-4 (June 1, 2005): 225–46. http://dx.doi.org/10.1127/zdgg/155/2005/225.

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Kovalenko, O. E. "Knowledge based design of convergent systems of situational management." Mathematical machines and systems 3 (2019): 67–74. http://dx.doi.org/10.34121/1028-9763-2019-3-67-74.

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Havlíček, J., J. Hron, and I. Tichá. "Knowledge based higher education." Agricultural Economics (Zemědělská ekonomika) 52, No. 3 (February 17, 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 refining or mining, above it. This schema satisfies specific needs of an organisation of warehouse data systems but it does not explain the role of these objects in the educational process. In education, the distinctions among data, information and knowledge need to be distinguished from the complex pedagogical point of view. Knowledge is the engine asking for more information and more data. Knowledge life cycle produces more information, more information asks for more data – that is: there is “just information”. Data, information and knowledge can be considered as object oriented measures assigned to real objects (entities). The following measures can be assigned to the objects: Measure of the zero order – name. Measure of the first order – data. Measure of the second order – information. Metrics of the third order – knowledge. Knowledge based curriculum involves knowledge into study plans and it considers knowledge as a distinctive part of study. Knowledge becomes the engine starting cycle of new information acquisition, reproduction and integration. The following problems have to be solved in building of knowledge based curriculum: Methodology and organisation of educational process. Technical support for knowledge based education. Evaluation and assessment of the process.
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Jahanshiri, E., and S. Walker. "Agricultural Knowledge-Based Systems at the Age of Semantic Technologies." International Journal of Knowledge Engineering-IACSIT 1, no. 1 (2015): 64–67. http://dx.doi.org/10.7763/ijke.2015.v1.11.

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Buchanan, Bruce G., Daniel Bobrow, Randall Davis, John McDermott, and Edward H. Shortliffe. "Knowledge-Based Systems." Annual Review of Computer Science 4, no. 1 (June 1990): 395–416. http://dx.doi.org/10.1146/annurev.cs.04.060190.002143.

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Kahn, M. G. "Knowledge-Based Systems." Yearbook of Medical Informatics 02, no. 01 (August 1993): 399–401. http://dx.doi.org/10.1055/s-0038-1637984.

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Mainzer, Klaus. "Knowledge-based systems." Journal for General Philosophy of Science 21, no. 1 (March 1990): 47–74. http://dx.doi.org/10.1007/bf01801416.

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DAVIS, R. "Knowledge-Based Systems." Science 231, no. 4741 (February 28, 1986): 957–63. http://dx.doi.org/10.1126/science.231.4741.957.

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Motoda, H., R. Mizoguchi, J. Boose, and B. Gaines. "Knowledge acquisition for knowledge-based systems." IEEE Expert 6, no. 4 (August 1991): 53–64. http://dx.doi.org/10.1109/64.85921.

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Müller-Kolck, Ulrich. "Knowledge acquisition for knowledge-based systems." Artificial Intelligence in Medicine 2, no. 2 (June 1990): 119–20. http://dx.doi.org/10.1016/0933-3657(90)90033-n.

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Dissertations / Theses on the topic "Knowledge based sysems"

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Kronberg, F., A. Weiner, T. Morgan, B. Stroozas, E. Girouard, A. Hopkins, L. Wong, M. James, J. Kneubuhl, and R. F. Malina. "Document Retrieval Triggered by Spacecraft Anomaly: Using the Kolodner Case-Based Reasoning (CBR) Paradigm to Design a Fault-Induced Response System." International Foundation for Telemetering, 1996. http://hdl.handle.net/10150/611459.

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International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California
We report on the initial design and development of a prototype computer-mediated response system, the Fault Induced Document Officer (FIDO), at the UC Berkeley Center for EUV Astrophysics (CEA) Extreme Ultraviolet Explorer project (EUVE). Typical 24x7 staffed spacecraft operations use highly skilled expert teams to monitor current ground systems and spacecraft state for responding to anomalous ground system and spacecraft conditions. Response to ground system error messages and spacecraft anomalies is based on knowledge of nominal component behavior and the evaluation of relevant telemetry by the team. This type of human-mediated operation is being replaced by an intelligent software system to reduce costs and to increase performance and reliability. FIDO is a prototype software application that will provide automated retrieval and display of documentation for operations staff. Initially, FIDO will be applied for ground systems. Later implementations of FIDO will target spacecraft systems. FIDO is intended to provide system state summary, links to relevant documentation, and suggestions for operator responses to error messages. FIDO will provide the operator with near realtime expert assistance and access to necessary information. This configuration should allow the resolution of many anomalies without the need for on-site intervention by a skilled controller or expert.
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Valdes, Francisco Javier. "Manufacturing compliance analysis for architectural design: a knowledge-aided feature-based modeling framework." Diss., Georgia Institute of Technology, 2016. http://hdl.handle.net/1853/54973.

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Given that achieving nominal (all dimensions are theoretically perfect) geometry is challenging during building construction, understanding and anticipating sources of geometric variation through tolerances modeling and allocation is critical. However, existing building modeling environments lack the ability to support coordinated, incremental and systematic specification of manufacturing and construction requirements. This issue becomes evident when adding multi-material systems produced off site by different vendors during building erection. Current practices to improve this situation include costly and time-consuming operations that challenge the relationship among the stakeholders of a project. As one means to overcome this issue, this research proposes the development of a knowledge-aided modeling framework that integrates a parametric CAD tool with a system modeling application to assess variability in building construction. The CAD tool provides robust geometric modeling capabilities, while System Modeling allows for the specification of feature-based manufacturing requirements aligned with construction standards and construction processes know-how. The system facilitates the identification of conflicting interactions between tolerances and manufacturing specifications of building material systems. The expected contributions of this project are the representation of manufacturing knowledge and tolerances interaction across off-site building subsystems to identify conflicting manufacturing requirements and minimize costly construction errors. The proposed approach will store and allocate manufacturing knowledge as Model-Based Systems Engineering (MBSE) design specifications for both single and multiple material systems. Also, as new techniques in building design and construction are beginning to overlap with engineering methods and standards (e.g. in-factory prefabrication), this project seeks to create collaborative scenarios between MBSE and Building Information Modeling (BIM) based on parametric, simultaneous, software integration to reduce human-to-data translation errors, improving model consistency among domains. Important sub-stages of this project include the comprehensive review of modeling and allocation of tolerances and geometric deviations in design, construction and engineering; an approach for model integration among System Engineering models, mathematical engines and BIM (CAD) models; and finally, a demonstration computational implementation of a System-level tolerances modeling and allocation approach.
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Roth-Berghofer, Thomas R. "Knowledge maintenance of case-based reasoning systems : the SIAM methodology /." Berlin : Akad. Verl.-Ges. Aka, 2003. http://www.loc.gov/catdir/toc/fy0804/2008299389.html.

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Lindner, Eli. "A framework for an innovative knowledge management system in knowlegde-based firms." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/71391/1/Eli_Lindner_Thesis.pdf.

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This study examined how a knowledge management system can bring innovative behaviour to a knowledge based firm. The study developed a framework for such a system by investigating what components should comprise the system and how they should interact. The outcome of the study is a recommended framework of components, tools & methods to effectively implement a knowledge management system.
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Aikenhead, Michael. "Legal knowledge-based systems : new directions in system design." Thesis, Durham University, 2001. http://etheses.dur.ac.uk/4384/.

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This thesis examines and critiques the concept of 'legal knowledge-based’ systems. Work on legal knowledge-based systems is dominated by work in 'artificial intelligence and law’. It seeks to automate the application of law and to automate the solution of legal problems. Automation however, has proved elusive. In contrast to such automation, this thesis proposes the creation of legal knowledge-based systems based on the concept of augmentation of legal work. Focusing on systems that augment legal work opens new possibilities for system creation and use. To inform how systems might augment legal work, this thesis examines philosophy, psychology and legal theory for information they provide on how processes of legal reasoning operate. It is argued that, in contrast to conceptions of law adopted in artificial intelligence and law, 'sensemaking' provides a useful perspective with which to create systems. It is argued that visualisation, and particularly diagrams, are an important and under considered element of reasoning and that producing systems that support diagramming of processes of legal reasoning would provide useful support for legal work. This thesis reviews techniques for diagramming aspects of sensemaking. In particular this thesis examines standard methods for diagramming arguments and methods for diagramming reasoning. These techniques are applied in the diagramming of legal judgments. A review is conducted of systems that have been constructed to support the construction of diagrams of argument and reasoning. Drawing upon these examinations, this thesis highlights the necessity of appropriate representations for supporting reasoning. The literature examining diagramming for reasoning support provides little discussion of appropriate representations. This thesis examines theories of representation for insight they can provide into the design of appropriate representations. It is concluded that while the theories of representation that are examined do not determine what amounts to a good representation, guidelines for the design and choice of representations can be distilled. These guidelines cannot map the class of legal knowledge-based systems that augment legal sensemaking, they can however, be used to explore this class and to inform construction of systems.
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Watson, Ian Duncan. "A methodology for knowledge analysis." Thesis, University of Liverpool, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.237515.

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Winfield, Michael James. "Multi-aspectual knowledge elicitation." Thesis, University of Salford, 2000. http://usir.salford.ac.uk/26965/.

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This work examines one of the major stumbling blocks of knowledge based systems development, namely knowledge elicitation. The challenge is a fundamental one of eliciting knowledge from domain experts including tacit knowledge. This thesis argues that, in the past, knowledge elicitation has been limited since elicitation has been performed from one or a limited number of aspects. A method is needed to assist in providing a pluralistic approach to knowledge elicitation that will aid multi-aspectual viewpoints of the domain knowledge to be elicited. MAKE (Multi-Aspectual Knowledge Elicitation) is such a pluralistic method. Using the work of Herman Dooyeweerd (1955) MAKE is developed from a sound philosophical basis. Two levels of knowledge are elicited using MAKE. The method starts by building a top-level knowledge map that covers all of the knowledge aspects and provides an overview of the domain. Such an overview determines the complexity of the domain allowing a knowledge based systems developer to see the effects of taking a minimalist approach to the development; that is the top-level map may be used to help define the scope of a system. The second level involves detailed knowledge elicitation. Using a process of abstraction, the concepts defined in each aspect are refined to a sufficiently detailed level to enable a system to be built. The resulting knowledge forms an ontological view of the domain knowledge. The empirical work adopting a case study approach has demonstrated that: MAKE can be used by people who are not necessarily versed in artificial intelligence techniques or in the philosophy of Dooyeweerd. MAKE has shown itself to be adaptable across a very varied set of domains MAKE is adaptable and useful for eliciting tacit knowledge. It is argued that MAKE indicates a change of direction from methods that are currently in use.
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Jones, S. R. "A comparison of knowledge elicitation techniques." Thesis, Cardiff University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368015.

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King, Brent. "Automatic extraction of knowledge from design data." Thesis, University of Sunderland, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.307964.

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Lagos, Nikolaos. "Knowledge-based product support systems." Thesis, Cardiff University, 2007. http://orca.cf.ac.uk/54573/.

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This research helps bridge the gap between conventional product support, where the support system is considered as a stand-alone application, and the new paradigm of responsive one, where the support system frequently communicates with its environment and reacts to stimuli. This new paradigm would enable product support knowledge to be captured, stored, processed, and updated automatically, being delivered to the users when, where and in the form they need it. The research reported in this thesis first defines Product Support Systems (PRSSs) as electronic means that provide accurate and up-to-date information to the user in a coherent and personalised manner. Product support knowledge is then identified as the integration of product, task, user, and support documentation knowledge. Next, the thesis focuses on an ontology-based model of the structure, relations, and attributes of product support knowledge. In that model product support virtual documentation (PSVD) is presented as an aggregation of Information Objects (IOs) and Information Object Clusters (IOCs). The description of PSVD is followed by an analysis of the relation between IOs, IOCs, and domain knowledge. Then, the thesis builds on the ontology-based representation of product support knowledge and explores the synergy between product support, problem solving, and knowledge engineering. As a result, a structured problem solving approach is introduced that combines case-based adaptation and model-based generation techniques. Based on that approach a knowledge engineering framework for product support systems is developed. A conceptual model of context-aware product support systems that extends the framework is then introduced. The conceptual model includes an ontology-based representation of knowledge related to the users, their activities, the support environment, and the device being used. An approach to semi-automatically integrating design and documentation data is also proposed as part of context-aware product support systems development process.
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Books on the topic "Knowledge based sysems"

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Steinke, Gerhard. Task-based security for knowledge base systems. Aachen: Verlag Shaker, 1992.

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Priti, Sajja, ed. Knowledge-based systems. Sudbury, Mass: Jones and Bartlett, 2010.

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Designing knowledge-based systems. Englewood Cliffs, N.J: Prentice-Hall, 1986.

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Designing knowledge-based systems. London: Kogan Page, 1985.

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R, Gaines Brian, and Boose John H, eds. Knowledge acquisition for knowledge-based systems. London: Academic Press, 1988.

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Aussenac, N., G. Boy, B. Gaines, M. Linster, J. G. Ganascia, and Y. Kodratoff, eds. Knowledge Acquisition for Knowledge-Based Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-57253-8.

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Central Computer and Telecommunications Agency., ed. Knowledge based systems volume. London: H.M.S.O., 1991.

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Partridge, D. Knowledge-based information systems. London: McGraw-Hill, 1995.

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Ramani, S., R. Chandrasekar, and K. S. R. Anjaneyulu, eds. Knowledge Based Computer Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/bfb0018363.

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Leondes, Cornelius T., ed. Intelligent Knowledge-Based Systems. Boston, MA: Springer US, 2005. http://dx.doi.org/10.1007/978-1-4020-7829-3.

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Book chapters on the topic "Knowledge based sysems"

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Micouin, Patrice. "Knowledge Systems." In Model-Based Systems Engineering, 41–58. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118579435.ch3.

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Bühmann, Lorenz, and Jens Lehmann. "Pattern Based Knowledge Base Enrichment." In Advanced Information Systems Engineering, 33–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41335-3_3.

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Shekhar, Shashi, and Hui Xiong. "Knowledge Based Systems." In Encyclopedia of GIS, 603. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_670.

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Beynon-Davies, Paul. "Knowledge Based Systems." In Information Systems Development, 116–23. London: Macmillan Education UK, 1998. http://dx.doi.org/10.1007/978-1-349-14931-5_14.

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Mohan, Chilukuri Krishna. "Knowledge-Based Systems." In Frontiers of Expert Systems, 1–18. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4509-5_1.

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Richter, Michael M. "Knowledge-Based Systems." In Intelligence and Artificial Intelligence, 109–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-03667-9_7.

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Graham, D. "Knowledge Elicitation." In Knowledge-Based Image Processing Systems, 27–40. London: Springer London, 1997. http://dx.doi.org/10.1007/978-1-4471-0635-7_3.

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Graham, D. "Knowledge Representation." In Knowledge-Based Image Processing Systems, 41–55. London: Springer London, 1997. http://dx.doi.org/10.1007/978-1-4471-0635-7_4.

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Fenton, Billy, T. M. McGinnity, and Liam P. Maguire. "Intelligent Systems Technology in the Fault Diagnosis of Electronic Systems." In Intelligent Knowledge-Based Systems, 1276–313. Boston, MA: Springer US, 2005. http://dx.doi.org/10.1007/978-1-4020-7829-3_36.

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Perraju, Tolety Siva, and Garimella Uma. "Mission Critical Intelligent Systems." In Intelligent Knowledge-Based Systems, 1184–210. Boston, MA: Springer US, 2005. http://dx.doi.org/10.1007/978-1-4020-7829-3_34.

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Conference papers on the topic "Knowledge based sysems"

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Matta, Nada, and Oswaldo Castillo Navetty. "Learning from Profession Knowledge: Application on Knitting." In Internet-Based Systems (SITIS 2009). IEEE, 2009. http://dx.doi.org/10.1109/sitis.2009.78.

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Widmann, K., I. Seeber, and R. Maier. "Mapping Knowledge Activities with System Operations to Foster Information Systems for Knowledge Work." In 2012 Eighth International Conference on Signal-Image Technology & Internet-Based Systems (SITIS 2012). IEEE, 2012. http://dx.doi.org/10.1109/sitis.2012.137.

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Despres, Sylvie, and Haifa Zargayouna. "Evaluation of Knowledge Based Applications: Benchmark and Guidelines." In Internet-Based Systems (SITIS 2009). IEEE, 2009. http://dx.doi.org/10.1109/sitis.2009.79.

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"KARE: Workshop on Knowledge Acquisition, Reuse and Evaluation." In Internet-Based Systems (SITIS 2009). IEEE, 2009. http://dx.doi.org/10.1109/sitis.2009.89.

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Ramona-Cristina, Popa, Andrei Vasilateanu, and Nicolae Goga. "Ontology based multi-system for SME knowledge workers." In 2016 IEEE International Symposium on Systems Engineering (ISSE). IEEE, 2016. http://dx.doi.org/10.1109/syseng.2016.7753132.

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Miled, A. Ben, D. Monticolo, V. Hilaire, and A. Koukam. "A Comparison of Knowledge Management Approaches Based on Multi Agent Systems." In Internet-Based Systems (SITIS 2009). IEEE, 2009. http://dx.doi.org/10.1109/sitis.2009.80.

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Petit, C., D. Schlegel, and S. Gomes. "Specification of a Knowledge Crossroads for a Productive and Optimised Design." In Internet-Based Systems (SITIS 2010). IEEE, 2010. http://dx.doi.org/10.1109/sitis.2010.63.

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Lahoud, Inaya, Davy Monticolo, and Samuel Gomes. "OCEAN: A Semantic Web Service to Extract Knowledge in E-Groupwares." In Internet-Based Systems (SITIS 2010). IEEE, 2010. http://dx.doi.org/10.1109/sitis.2010.64.

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Finch, I. "Knowledge-based systems, viewpoints and the World Wide Web." In IEE Colloquium on Web-Based Knowledge Servers. IEE, 1998. http://dx.doi.org/10.1049/ic:19980536.

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Plantie, Michel, and P. Riccio. "Knowledge Cartography and Social Network Representation: Application to Collaborative Platforms in Scientific Area." In Internet-Based Systems (SITIS 2010). IEEE, 2010. http://dx.doi.org/10.1109/sitis.2010.45.

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Reports on the topic "Knowledge based sysems"

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Chandrasekaran, B. Distributed Knowledge-Based Systems. Fort Belvoir, VA: Defense Technical Information Center, March 1989. http://dx.doi.org/10.21236/ada211984.

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Feigenbaum, Edward A., Robert S. Engelmore, and Paul C. Rosenbloom. Knowledge-Based Systems Research. Fort Belvoir, VA: Defense Technical Information Center, August 1990. http://dx.doi.org/10.21236/ada277505.

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Feigenbaum, Edward A., Robert S. Engelmore, and Paul C. Rosenbloom. Knowledge-Based Systems Research. Fort Belvoir, VA: Defense Technical Information Center, August 1990. http://dx.doi.org/10.21236/ada225816.

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Pasquale, Joseph. Knowledge-Based Distributed Systems Management. Fort Belvoir, VA: Defense Technical Information Center, June 1986. http://dx.doi.org/10.21236/ada619313.

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Stengel, Robert F. Knowledge-Based Systems for Computational Control. Fort Belvoir, VA: Defense Technical Information Center, November 1992. http://dx.doi.org/10.21236/ada260409.

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Lunt, Teresa F., and Thomas D. Garvey. Multilevel Security for Knowledge Based Systems. Fort Belvoir, VA: Defense Technical Information Center, December 1990. http://dx.doi.org/10.21236/ada234974.

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Cuginia, John V. Programming languages for knowledge-based systems. Gaithersburg, MD: National Bureau of Standards, 1987. http://dx.doi.org/10.6028/nbs.sp.500-145.

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Heggestad, Harold M. Knowledge-Based System Analysis and Control. Fort Belvoir, VA: Defense Technical Information Center, September 1986. http://dx.doi.org/10.21236/ada188163.

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Heggestad, Harold M. Knowledge-Based System Analysis and Control. Fort Belvoir, VA: Defense Technical Information Center, September 1991. http://dx.doi.org/10.21236/ada249611.

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Garrett, R. G., and A. G. Fabbri. Introduction, Intelligent information management: knowledge-based systems. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1994. http://dx.doi.org/10.4095/193922.

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