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Collective intelligence has become one of major research issues
studied by today's and future computer science. Computational
collective intelligence is understood as this form of group
intellectual activity that emerges from collaboration and compe-
tion of many artificial individuals. Robotics, artificial
intelligence, artificial cognition and group working try to create
efficient models for collective intelligence in which it emerges
from sets of actions carried out by more or less intelligent
individuals. The major methodological, theoretical and practical
aspects underlying computational collective intelligence are group
decision making, collective action coordination, collective
competition and knowledge description, transfer and integration.
Obviously, the application of multiple computational technologies
such as fuzzy systems, evo- tionary computation, neural systems,
consensus theory, knowledge representation etc. is necessary to
create new forms of computational collective intelligence and
support existing ones. Three subfields of application of
computational technologies to support forms of collective
intelligence are of special attention to us. The first one is
semantic web treated as an advanced tool that increases the
collective intelligence in networking environments. The second one
covers social networks modeling and analysis, where social networks
are this area of in which various forms of computational collective
intelligence emerges in a natural way. The third subfield relates
us to agent and mul- agent systems understood as this computational
and modeling paradigm which is especially tailored to capture the
nature of computational collective intelligence in populations of
autonomous individuals.
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Intelligent Information and Database Systems - Third International Conference, ACIIDS 2011, Daegu, Korea, April 20-22, 2011, Proceedings, Part I (Paperback, 2011 Ed.)
Ngoc Thanh Nguyen, Chong-Gun Kim, Adam Janiak
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R1,677
Discovery Miles 16 770
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Ships in 10 - 15 working days
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The two-volume set LNAI 6591 and LNCS 6592 constitutes the refereed
proceedings of the Third International Conference on Intelligent
Information and Database Systems, ACIIDS 2011, held in Daegu,
Korea, in April 2011. The 110 revised papers presented together
with 2 keynote speeches were carefully reviewed and selected from
310 submissions. The papers are thematically divided into two
volumes; they cover the following topics: intelligent database
systems, data warehouses and data mining, natural language
processing and computational linguistics, semantic Web, social
networks and recommendation systems, technologies for intelligent
information systems, collaborative systems and applications,
e-business and e-commerce systems, e-learning systems, information
modeling and requirements engineering, information retrieval
systems, intelligent agents and multi-agent systems, intelligent
information systems, intelligent internet systems, intelligent
optimization techniques, object-relational DBMS, ontologies and
knowledge sharing, semi-structured and XML database systems,
unified modeling language and unified processes, Web services and
semantic Web, computer networks and communication systems.
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Intelligent Information and Database Systems - Third International Conference, ACIIDS 2011, Daegu, Korea, April 20-22, 2011, Proceedings, Part II (Paperback, 2011 ed.)
Ngoc Thanh Nguyen, Chong-Gun Kim, Adam Janiak
|
R3,101
Discovery Miles 31 010
|
Ships in 10 - 15 working days
|
The two-volume set LNAI 6591 and LNCS 6592 constitutes the refereed
proceedings of the Third International Conference on Intelligent
Information and Database Systems, ACIIDS 2011, held in Daegu,
Korea, in April 2011. The 110 revised papers presented together
with 2 keynote speeches were carefully reviewed and selected from
310 submissions. The papers are thematically divided into two
volumes; they cover the following topics: intelligent database
systems, data warehouses and data mining, natural language
processing and computational linguistics, semantic Web, social
networks and recommendation systems, technologies for intelligent
information systems, collaborative systems and applications,
e-business and e-commerce systems, e-learning systems, information
modeling and requirements engineering, information retrieval
systems, intelligent agents and multi-agent systems, intelligent
information systems, intelligent internet systems, intelligent
optimization techniques, object-relational DBMS, ontologies and
knowledge sharing, semi-structured and XML database systems,
unified modeling language and unified processes, Web services and
semantic Web, computer networks and communication systems.
Collective intelligence has become one of major research issues
studied by today's and future computer science. Computational
collective intelligence is understood as this form of group
intellectual activity that emerges from collaboration and compe-
tion of many artificial individuals. Robotics, artificial
intelligence, artificial cognition and group working try to create
efficient models for collective intelligence in which it emerges
from sets of actions carried out by more or less intelligent
individuals. The major methodological, theoretical and practical
aspects underlying computational collective intelligence are group
decision making, collective action coordination, collective
competition and knowledge description, transfer and integration.
Obviously, the application of multiple computational technologies
such as fuzzy systems, evo- tionary computation, neural systems,
consensus theory, knowledge representation etc. is necessary to
create new forms of computational collective intelligence and
support existing ones. Three subfields of application of
computational technologies to support forms of collective
intelligence are of special attention to us. The first one is
semantic web treated as an advanced tool that increases the
collective intelligence in networking environments. The second one
covers social networks modeling and analysis, where social networks
are this area of in which various forms of computational collective
intelligence emerges in a natural way. The third subfield relates
us to agent and mul- agent systems understood as this computational
and modeling paradigm which is especially tailored to capture the
nature of computational collective intelligence in populations of
autonomous individuals.
|
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