Agent-Mediated Knowledge Management
Subtitle: International Symposium AMKM 2003, Stanford, CA, USA, March 24-26, 2003, Revised and Invited Papers (Lecture Notes in Computer Science)
Contributors: Ludger van Elst (Editor); Andreas Abecker (Editor); Virginia Dignum (Editor)
Edition: 1 edition
Publisher: Springer
Published: March 19, 2004
Language: eng
Format: Paperback
Number of pages: 428
ISBN-13: 9783540208686
Subjects: Knowledge-based systems / expert systems; Intelligent agents (Computer software); Computers - General Information; Computer Books: General; Computers; Intelligent agents (Computer s; Information Storage & Retrieval; Congresses; Artificial Intelligence - General; Expert Systems; Computers / Artificial Intelligence; Knowledge management; Computer Science; Agents intelligents (Logiciels); Congráes
First sentence: Knowledge Management (KM) is defined as a systematic, holistic approach for sustain-ably improving the handling of knowledge on all levels of an organization (individual, group, organizational, and inter-organizational level) in order to support the organization's business goals, such as innovation, quality, cost effectiveness etc. (cp. [33]).
Description: In this book, we present a collection of papers around the topic of Agent- Mediated Knowledge Management. Most of the papers are extended and - provedversions of work presented at the symposium on Agent-Mediated Kno- edge Management held during the AAAI Spring Symposia Series in March 2003 at Stanford University. The aim of the Agent-Mediated Knowledge Management symposium was to bring together researchers and practitioners of the ?elds of KM and agent te- nologiestodiscussthebene?ts,possibilitiesandadded-valueofcross-fertilization. Knowledge Management (KM) has been a predominant trend in bu- ness in recent years. Not only is Knowledge Management an important ?eld of applicationfor AIandrelatedtechniques,suchasCBRtechnologyforintelligent lessons-learned systems, it also provides new challenges to the AI community, like, for example, context-aware knowledge delivery. Scaling up research pro- typestoreal-worldsolutionsusuallyrequiresanapplication-drivenintegrationof several basic technologies, e.g., ontologies for knowledge sharing and reuse, c- laboration support like CSCW systems, and personalized information services. Typical characteristics to be dealt with in such an integration are: – manifold, logically and physically dispersed actors and knowledge sources, – di?erent degrees of formalization of knowledge, – di?erent kinds of (Web-based) services and (legacy) systems, – con?icts between local (individual) and global (group or organizational) goals.