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Knowledge organization literature. Selected items
Your search for
class 157 Computerisation of Thought Processes, Knowledge-Based Systems
found the 11 items below.
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Items on this class as the base theme
Chen, Z., Lu, K. – A preprocess algorithm of filtering irrelevant information based on the minimum class difference (Lang.: eng). - In: Knowledge-based Systems, 19(2006)6, p.422-429. Al-Obeidat, Feras et al. – Differential evolution for learning the classification method PROAFTN (Lang.: eng). - In: Knowledge-based systems, 23(2010)5, pp. 418-426. Rasmussen, J.; Goodstein, L.P.; Pejtersen, A.M.. – Cognitive systems engineering (Lang.: eng). - Chichester, Sussex, Wiley & Sons, 1994. – pp. 352. Cognitive systems engineering is the discipline underlying the design of computer-based information systems to support human work and endeavor. The book describes a cross-disciplinary framework for the integration of model concepts from many different disciplines, such as engineering, psychology, cognitive science, management science, information and computer-science. It is based on actual work performance in several domains.Cherkassky, V.; Vassilas, N., Wechsler, H. – Semantic categorization using a hierachical associative memory (Lang.: eng). - In: Int.J.of Neural Networks.Vol.2.No.2-4.1991.p.101-114. Schuwer, R.V.; Kusters, R.J. – Application areas and added value of knowledge base systems (Lang.: eng). - In: Inform.& Management.Vol.24.1993.p.83-92. Cherkassky, V.; Vassilas, N., Wechsler, H.. – Semantic categorization using a hierachical associative memory (Lang.: eng). - In: Int.J.of Neural Networks. Vol. 2. No. 2-4. p.101-114. Schuwer, R.V.; Kusters, R.J.. – Application areas and added value of knowledge base systems (Lang.: eng). - In: Inform.& Management. Vol. 24. p.83-92. | 10859 1990-0886 | 157, 715, 757 |
Special Issue: Case-based reasoning and its applications (Lang.: eng). - In: Expert Systems with Applicat.Vol.6.No.1.1993.p.1-104. The idea of Case-Based Reasoning (CBR) is to store experience as cases in a case base.When a new problem is encountered, the system uses memory of relevant past cases to interpret or solve the problem.As a result, the more cases the system stores the b etter it performs.This issue contains nine articles on CBR with a guest-editors note from Ting-Peng Liang and Efraim Turban| 11619 1993-0886 | 157, 715, 757 |
Special Issue: Case-based reasoning and its applications (Lang.: eng). - In: Expert Systems with Applicat.. Vol. 6. No. 1. p.1-104. The idea of Case-Based Reasoning (CBR) is to store experience as cases in a case base. When a new problem is encountered, the system uses memory of relevant past cases to interpret or solve the problem. As a result, the more cases the system stores the better it performs. This issue contains nine articles on CBR with a guest-editors note from Ting-Peng Liang and Efraim Turban.
Further items on this class as a particular theme
Mak, B.; Lytinen, K. – A model to access the behavioral impacts of consultative knowledge based systems (Lang.: ). – In: Information Processing & Management 1997(33)4,p. 539-550. Hernándex, F., Agenjo, X. – La utilización de sistemas basados en el conocimiento para la mejora de la calidad de la información bibliográfica [Using knowledge-based systems to improve the quality of bibliographic information] (Lang.: spa). – In: Organización del Conociemto en Sistemas de Información y Documentación, 2(1997),p.223-224.
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