Relevant bibliographies by topics / Bases of systems of knowledge

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  2. Dissertations / Theses
  3. Books
  4. Book chapters
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Academic literature on the topic 'Bases of systems of knowledge'

Author: Grafiati
Published: 4 June 2021
Last updated: 2 February 2022

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Journal articles on the topic "Bases of systems of knowledge"

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Subrahmanian, V. S. "Amalgamating knowledge bases." ACM Transactions on Database Systems 19, no. 2 (1994): 291–331. http://dx.doi.org/10.1145/176567.176571.

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Šilerová, E., and L. Kučírková. "Knowledge and information systems." Agricultural Economics (Zemědělská ekonomika) 54, No. 5 (2008): 217–23. http://dx.doi.org/10.17221/245-agricecon.

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We can see that the today’s management level of informations is not quite fully controlled in most businesses. Nowadays generation of information systems creates support for business processes with the aim of optimalization of these processes on the bases of experiences with similar business processes. Today’s information systems are at the level of data management or information management. Quite a few manage information processes in the area of tactical and strategic planning and almost no one manages processes in the areas of gathering, distribution and sharing of knowledge in business. We
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Evgenev, G. B. "Synergetic knowledge bases." Ontology of designing 11, no. 1 (2021): 76–88. http://dx.doi.org/10.18287/2223-9537-2021-11-1-76-88.

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Modern knowledge bases must largely correspond to human thinking and the reality of the world. Synergetic knowledge bases create the possibility of joint use of both "hard" computing, which require the accuracy and unique-ness of the solution, and "soft" computing, allowing a given error and uncertainty for a specific problem. A methodolo-gy for creating synergetic systems for the representation of knowledge using artificial intelligence technologies is pro-posed. The methodology is based on knowledge base methods and can be used to develop design and management systems in industries. A model
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Lorentzos, N. A., C. P. Yialouris, and A. B. Sideridis. "Time-evolving rule-based knowledge bases." Data & Knowledge Engineering 29, no. 3 (1999): 313–35. http://dx.doi.org/10.1016/s0169-023x(98)00048-2.

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García-Manotas, Ignacio, Eduardo Lupiani, Francisco García-Sánchez, and Rafael Valencia-García. "Populating Knowledge Based Decision Support Systems." International Journal of Decision Support System Technology 2, no. 1 (2010): 1–20. http://dx.doi.org/10.4018/jdsst.2010101601.

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Knowledge-based decision support systems (KBDSS) hold up business and organizational decision-making activities on the basis of the knowledge available concerning the domain under question. One of the main problems with knowledge bases is that their construction is a time-consuming task. A number of methodologies have been proposed in the context of the Semantic Web to assist in the development of ontology-based knowledge bases. In this paper, we present a technique for populating knowledge bases from semi-structured text which take advantage of the semantic underpinnings provided by ontologie
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Vostrovský, V. "Expert systems utilization in knowledge management ." Agricultural Economics (Zemědělská ekonomika) 52, No. 10 (2012): 451–55. http://dx.doi.org/10.17221/5050-agricecon.

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Knowledge and information are the key to successful pursuit of business activity. For the management knowledge, there can be employed among others the expert systems and eLearning. The article provides the expert systems utilization in knowledge management as the expert eLearning component. This solution then makes it possible to preserve the appropriate set of knowledge for a given business activity in knowledge bases and to pass this knowledge in the moment of need in the form of multimedia teaching applications to the appropriate employees.  
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Santos, Eugene, and Hang T. Dinh. "On automatic knowledge validation for Bayesian knowledge bases." Data & Knowledge Engineering 64, no. 1 (2008): 218–41. http://dx.doi.org/10.1016/j.datak.2007.07.004.

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Nowak-Brzezińska, Agnieszka, and Alicja Wakulicz-Deja. "Exploration of rule-based knowledge bases: A knowledge engineer’s support." Information Sciences 485 (June 2019): 301–18. http://dx.doi.org/10.1016/j.ins.2019.02.019.

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Hao, Shuang, Nan Tang, Guoliang Li, Jian Li, and Jianhua Feng. "Distilling relations using knowledge bases." VLDB Journal 27, no. 4 (2018): 497–519. http://dx.doi.org/10.1007/s00778-018-0506-9.

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Bouzar-Benlabiod, Lydia, Salem Benferhat, and Thouraya Bouabana-Tebibel. "Comparing and Weakening Possibilistic Knowledge Bases." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 22, no. 02 (2014): 181–203. http://dx.doi.org/10.1142/s0218488514500081.

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Weighted logics are important tools for reasoning under uncertain knowledge. A weighted knowledge base is a set of weighted formulas of the form (φi, αi) where φi is a propositional formula and αi is the certainty degree associated with φi. This paper addresses two issues in the possibility theory framework: i) how to compare two weighted knowledge bases with respect to their information contents? and ii) how to syntactically define the concept of forgetting variables? We show that comparing knowledge bases is the counterpart of the concept of the specificity relation defined between possibili
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Dissertations / Theses on the topic "Bases of systems of knowledge"

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Richardson, Matthew. "Learning and inference in collective knowledge bases /." Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/6926.

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Cuddihy, Paul. "Compiling GEN-X knowledge bases into "C" /." Online version of thesis, 1991. http://hdl.handle.net/1850/10792.

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Cintra, Marcos Evandro. "Genetic generation of fuzzy knowledge bases: new perspectives." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-16072012-144620/.

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This work focus on the genetic generation of fuzzy systems. One of the main contribution of this work is the proposal of the FCA-BASED method, which generates the genetic search space using the formal concept analysis theory by extracting rules from data. The experimental evaluation results of the FCA-BASED method show its robustness, producing a good trade-off between the accuracy and the interpretability of the generated models. Moreover, the FCA-BASED method presents improvements to the DOC-BASED method, a previously proposed approach, related to the reduction of the computational cost for
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Abbas, Assad. "Identifying design issues related to the knowledge bases of medical decision support systems." Thesis, University of Skövde, School of Humanities and Informatics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-4014.

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<p>The modern medical diagnostic systems are based on the techniques using digital data formats – a natural feed for the computer based systems. With the use of modern diagnostic techniques the diagnosis process is becoming more complex as many diseases seem to have the same pre-symptoms at early stages. And of course computer based systems require more efficient and effective ways to identify such complexities. However, the existing formalisms for knowledge representation, tools and technologies, learning and reasoning strategies seem inadequate to create meaningful relationship among the ent
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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-
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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 lega
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Yoon, Changwoo. "Domain-specific knowledge-based informational retrieval model using knowledge reduction." [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0011560.

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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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Pilkington, R. "Knowledge-based systems in topic learning." Thesis, University of Leeds, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.380324.

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May, John Hendy Robert. "Knowledge-based systems in engineering safety." Thesis, University of Bristol, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327937.

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Books on the topic "Bases of systems of knowledge"

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Karagiannis, D. Knowledge selection in large knowledge bases. FAW Ulm, 1991.

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Hannu, Jaakkola, Kiyoki Yasushi, and Tokuda Takahiro, eds. Information modelling and knowledge bases XIX. IOS Press, 2008.

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European-Japanese Conference on Information Modelling and Knowledge Bases (18th 2008). Information modelling and knowledge bases XX. IOS Press, 2009.

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2010), European-Japanese Conference on Information Modelling and Knowledge Bases (20th. Information modelling and knowledge bases XXII. Ios Press, 2011.

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Gerhard, Lakemeyer, ed. The logic of knowledge bases. MIT Press, 2000.

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Rathmann, Peter. Nonmonotonic semantics for partitioned knowledge bases. Dept. of Computer Science, Stanford University, 1991.

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Leite, João Alexandre. Evolving knowledge bases: Specification and semantics. IOS Press, 2003.

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Allen, Ginsberg. Automatic refinement of expert system knowledge bases. Pitman, 1988.

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

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Ullman, Jeffrey D. Principles of database and knowledge-base systems.: Classical database systems. Computer Science Press, 1988.

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Book chapters on the topic "Bases of systems of knowledge"

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Brodie, Michael L., and John Mylopoulos. "Knowledge Bases vs Databases." In Topics in Information Systems. Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4612-4980-1_9.

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van der Lubbe, J. C. A., E. Backer, and W. Krijgsman. "Models for reasoning with multitype uncertainty in expert systems." In Uncertainty in Knowledge Bases. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/bfb0028125.

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Kim, Yang Sok, Byeong Ho Kang, Seung Hwan Ryu, Paul Compton, Soyeon Caren Han, and Tim Menzies. "Crowd-Sourced Knowledge Bases." In Knowledge Management and Acquisition for Intelligent Systems. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32541-0_23.

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Sleeman, Derek, Yi Zhang, and Wamberto Vasconcelos. "Characterisation of Knowledge Bases." In Applications and Innovations in Intelligent Systems XI. Springer London, 2004. http://dx.doi.org/10.1007/978-1-4471-0643-2_17.

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Polyachenko, Boris E., Filipp I. Andon, and Oleg L. Gunko. "Data Bases, Knowledge Bases and Intelligent Information Systems." In Systems Thinking in Europe. Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-3748-9_68.

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Israel, David. "AI Knowledge Bases And Databases." In Topics in Information Systems. Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4612-4980-1_7.

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Machado, Ricardo José, and Armando Freitas Da Rocha. "The combinatorial neural network: A connectionist model for knowledge based systems." In Uncertainty in Knowledge Bases. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/bfb0028145.

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Karagiannis, Dimitris, Franz J. Kurfeß, and Heinz-Wilhelm Schmidt. "Knowledge selection in large knowledge bases." In The Next Generation of Information Systems: From Data to Knowledge. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-55616-8_54.

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

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Xiao, Guohui, and Thomas Eiter. "Inline Evaluation of Hybrid Knowledge Bases." In Web Reasoning and Rule Systems. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23580-1_28.

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Conference papers on the topic "Bases of systems of knowledge"

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Torres, Néstor Manuel Garzón, and Luis Carlos Torres Soler. "Knowledge bases." In 13th CONTECSI International Conference on Information Systems and Technology Management. TECSI, 2016. http://dx.doi.org/10.5748/9788599693124-13contecsi/rf-3911.

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Nowak - Brzezinska, Agnieszka. "Outlier mining in rule-based knowledge bases." In 2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA). IEEE, 2017. http://dx.doi.org/10.1109/inista.2017.8001192.

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Fiol-Roig, Gabriel. "On Discovering Qualitative Knowledge in Rule Based Knowledge Bases: An Intelligent Approach." In 2020 15th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, 2020. http://dx.doi.org/10.23919/cisti49556.2020.9141058.

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Nguyen, Van Tham, and Trong Hieu Tran. "Inconsistency measures for probabilistic knowledge bases." In 2017 9th International Conference on Knowledge and Systems Engineering (KSE). IEEE, 2017. http://dx.doi.org/10.1109/kse.2017.8119450.

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Santos, Eugene, Qi Gu, and Eunice E. Santos. "Incomplete information and Bayesian Knowledge-Bases." In 2011 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2011. http://dx.doi.org/10.1109/icsmc.2011.6084155.

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Ren, Yong, Wenyu Zheng, and Yan Ren. "Construction and Application of Knowledge Bases." In 2020 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS). IEEE, 2020. http://dx.doi.org/10.1109/icpics50287.2020.9202026.

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Yongjie Zhang and Ansheng Deng. "Redundancy rules reduction in rule-based knowledge bases." In 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2015. http://dx.doi.org/10.1109/fskd.2015.7382017.

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Zenkert, Johannes, Alexander Holland, and Madjid Fathi. "Discovering contextual knowledge with associated information in dimensional structured knowledge bases." In 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2016. http://dx.doi.org/10.1109/smc.2016.7844520.

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Dagli and Hoffman. "Application of distributed knowledge bases in intelligent manufacturing." In IEEE International Conference on Systems Engineering. IEEE, 1989. http://dx.doi.org/10.1109/icsyse.1989.48663.

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Pikalov, Yurii. "Noospheric Way of Organizing Knowledge in the Knowledge Bases of Innovate Importance." In 11th International Conference on Knowledge Management and Information Systems. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0008347302500257.

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Reports on the topic "Bases of systems of knowledge"

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

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Chandrasekaran, B. Distributed Knowledge-Based Systems. Defense Technical Information Center, 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. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada225816.

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

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Weiss, Sholom M., and Casimir A. Kulikowski. Empirical Analysis and Refinement of Expert System Knowledge Bases. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada200146.

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Weiss, Sholom M., and Casimir A. Kulikowski. Empirical Analysis and Refinement of Expert System Knowledge Bases. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada203607.

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Stengel, Robert F. Knowledge-Based Systems for Computational Control. Defense Technical Information Center, 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. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada234974.

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

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Minker, Jack. Deductive Databases and Knowledge Base Systems. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada295498.

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