Intelligent Information Processing IV: 5th IFIP International Conference on Intelligent Information Processing, October 19-22, 2008, Beijing, China - Couverture souple
Synopsis
Knowledge existing in modern information systems usually comes from many sources and is mapped in many ways. There is a real need for representing “knowledge pieces” as rather universal objects that should fit to multi-purpose a- ing systems. According to great number of information system’s tasks, knowledge representation is more or less detailed (e.g. some level of its granularity is - sumed). The main goal of this paper is to present chosen aspects of expressing granularity of knowledge implemented in intelligent systems. One of the main r- sons of granularity phenomena is diversification of knowledge sources, therefore the next section is devoted to this issue. 2. Heterogeneous Knowledge as a Source for Intelligent Systems Knowledge, the main element of so-called intelligent applications and systems, is very often heterogeneous. This heterogeneity concerns the origin of knowledge, its sources as well as its final forms of presentation. In this section the selected c- teria of knowledge differentiation will be presented, in the context of potential sources of knowledge acquisition. In Fig. 1 an environment of intelligent systems is shown, divided into different knowledge sources for the system. Fig. 1. Potential knowledge sources for intelligent information/reasoning system. Source: own elaboration based on (Mach, 2007) p. 24.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Knowledge existing in modern information systems usually comes from many sources and is mapped in many ways. There is a real need for representing 'knowledge pieces' as rather universal objects that should fit to multi-purpose a- ing systems. According to great number of information system's tasks, knowledge representation is more or less detailed (e.g. some level of its granularity is - sumed). The main goal of this paper is to present chosen aspects of expressing granularity of knowledge implemented in intelligent systems. One of the main r- sons of granularity phenomena is diversification of knowledge sources, therefore the next section is devoted to this issue. 2. Heterogeneous Knowledge as a Source for Intelligent Systems Knowledge, the main element of so-called intelligent applications and systems, is very often heterogeneous. This heterogeneity concerns the origin of knowledge, its sources as well as its final forms of presentation. In this section the selected c- teria of knowledge differentiation will be presented, in the context of potential sources of knowledge acquisition. In Fig. 1 an environment of intelligent systems is shown, divided into different knowledge sources for the system. Fig. 1. Potential knowledge sources for intelligent information/reasoning system. Source: own elaboration based on (Mach, 2007) p. 24. 280 pp. Englisch. N° de réf. du vendeur 9781441946867
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Taschenbuch. Etat : Neu. Intelligent Information Processing IV | 5th IFIP International Conference on Intelligent Information Processing, October 19-22, 2008, Beijing, China | Eunikka Mercier-Laurent (u. a.) | Taschenbuch | IFIP Advances in Information and Communication Technology | xi | Englisch | 2010 | Springer | EAN 9781441946867 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 107219301
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Knowledge existing in modern information systems usually comes from many sources and is mapped in many ways. There is a real need for representing ¿knowledge pieces¿ as rather universal objects that should fit to multi-purpose a- ing systems. According to great number of information system¿s tasks, knowledge representation is more or less detailed (e.g. some level of its granularity is - sumed). The main goal of this paper is to present chosen aspects of expressing granularity of knowledge implemented in intelligent systems. One of the main r- sons of granularity phenomena is diversification of knowledge sources, therefore the next section is devoted to this issue. 2. Heterogeneous Knowledge as a Source for Intelligent Systems Knowledge, the main element of so-called intelligent applications and systems, is very often heterogeneous. This heterogeneity concerns the origin of knowledge, its sources as well as its final forms of presentation. In this section the selected c- teria of knowledge differentiation will be presented, in the context of potential sources of knowledge acquisition. In Fig. 1 an environment of intelligent systems is shown, divided into different knowledge sources for the system. Fig. 1. Potential knowledge sources for intelligent information/reasoning system. Source: own elaboration based on (Mach, 2007) p. 24.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 280 pp. Englisch. N° de réf. du vendeur 9781441946867
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Knowledge existing in modern information systems usually comes from many sources and is mapped in many ways. There is a real need for representing 'knowledge pieces' as rather universal objects that should fit to multi-purpose a- ing systems. According to great number of information system's tasks, knowledge representation is more or less detailed (e.g. some level of its granularity is - sumed). The main goal of this paper is to present chosen aspects of expressing granularity of knowledge implemented in intelligent systems. One of the main r- sons of granularity phenomena is diversification of knowledge sources, therefore the next section is devoted to this issue. 2. Heterogeneous Knowledge as a Source for Intelligent Systems Knowledge, the main element of so-called intelligent applications and systems, is very often heterogeneous. This heterogeneity concerns the origin of knowledge, its sources as well as its final forms of presentation. In this section the selected c- teria of knowledge differentiation will be presented, in the context of potential sources of knowledge acquisition. In Fig. 1 an environment of intelligent systems is shown, divided into different knowledge sources for the system. Fig. 1. Potential knowledge sources for intelligent information/reasoning system. Source: own elaboration based on (Mach, 2007) p. 24. N° de réf. du vendeur 9781441946867
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