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Item Details
Title: INTELLIGENT INFORMATION PROCESSING IV
5TH IFIP INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION PROCESSING, OCTOBER 19-22, 2008, BEIJING, CHINA
By: Zhongzhi Shi (Editor), Eunika Mercier-Laurent (Editor), David B. Leake (Editor)
Format: Hardback

List price: £109.99


We currently do not stock this item, please contact the publisher directly for further information.

ISBN 10: 0387876847
ISBN 13: 9780387876849
Publisher: SPRINGER-VERLAG NEW YORK INC.
Pub. date: 1 September, 2008
Edition: 2008 ed.
Series: IFIP Advances in Information and Communication Technology 288
Pages: 267
Description: Constitutes the refereed proceedings of the 5th IFIP International Conference on Intelligent Information Processing held in Beijing, China on October 19-22, 2008. This work covers topics including: foundations of computer science; software theory and practice; education; communication systems; information systems; and, computer systems technology.
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.
Illustrations: 36 Tables, black and white; XI, 267 p.
Publication: US
Imprint: Springer-Verlag New York Inc.
Returns: Returnable
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