Intelligent Information Processing IV

Intelligent Information Processing IV

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Knowledge existing in modern information systems usually comes from many sources and is mapped in many ways. There is a real need for representing a€œknowledge piecesa€ as rather universal objects that should fit to multi-purpose a- ing systems. According to great number of information systema€™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.Generating. OWL. Ontology. from. ER. Diagram. Muhammad Fahad Mohammad Ali Jinnah University, Islamabad, ... been documented in structural analysis and structured design (SASD), especially in simple or Extended ER Diagram (ERD).


Title:Intelligent Information Processing IV
Author: Zhongzhi Shi, Eunikka Mercier-Laurent, David Leake
Publisher:Springer Science & Business Media - 2008-09-29
ISBN-13:

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