|
|
|
|
| LEADER |
05374nmm a2200433 u 4500 |
| 001 |
EB000378839 |
| 003 |
EBX01000000000000000231891 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
130626 ||| eng |
| 020 |
|
|
|a 9783540728399
|
| 100 |
1 |
|
|a Gorodetsky, Vladimir
|e [editor]
|
| 245 |
0 |
0 |
|a Autonomous Intelligent Systems: Multi-Agents and Data Mining
|h Elektronische Ressource
|b Second International Workshop, AIS-ADM 2007, St. Petersburg, Russia, June 3-5, 2007, Proceedings
|c edited by Vladimir Gorodetsky, Chengqi Zhang, Victor Skormin, Longbing Cao
|
| 250 |
|
|
|a 1st ed. 2007
|
| 260 |
|
|
|a Berlin, Heidelberg
|b Springer Berlin Heidelberg
|c 2007, 2007
|
| 300 |
|
|
|a XIV, 326 p
|b online resource
|
| 505 |
0 |
|
|a Invited Talks -- Peer-to-Peer Data Mining, Privacy Issues, and Games -- Ontos Solutions for Semantic Web: Text Mining, Navigation and Analytics -- Robust Agent Communities -- WI Based Multi-aspect Data Analysis in a Brain Informatics Portal -- Agent and Data Mining -- Agent-Mining Interaction: An Emerging Area -- Evaluating Knowledge Intensive Multi-agent Systems -- Towards an Ant System for Autonomous Agents -- Semantic Modelling in Agent-Based Software Development -- Combination Methodologies of Multi-agent Hyper Surface Classifiers: Design and Implementation Issues -- Security in a Mobile Agent Based DDM Infrastructure -- Automatic Extraction of Business Rules to Improve Quality in Planning and Consolidation in Transport Logistics Based on Multi-agent Clustering -- Intelligent Agents for Real Time Data Mining in Telecommunications Networks -- Architecture of Typical Sensor Agent for Learning and Classification Network -- Self-organizing Multi-agent Systems for Data Mining --
|
| 505 |
0 |
|
|a Chinese Weblog Pages Classification Based on Folksonomy and Support Vector Machines
|
| 505 |
0 |
|
|a Role-Based Decision Mining for Multiagent Emergency Response Management -- Agent Competition and Data Mining -- Virtual Markets: Q-Learning Sellers with Simple State Representation -- Fusion of Dependence Networks in Multi-agent Systems - Application to Support Net-Enabled Littoral Surveillance -- Multi-agent Framework for Simulation of Adaptive Cooperative Defense Against Internet Attacks -- On Competing Agents Consistent with Expert Knowledge -- On-Line Agent Teamwork Training Using Immunological Network Model -- Text Mining, Semantic Web, and Agents -- Combination of Rough Sets and Genetic Algorithms for Text Classification -- Multi-agent Meta-search Engine Based on Domain Ontology -- Efficient Search Technique for Agent-Based P2P Information Retrieval -- Classification of Web Documents Using Concept Extraction from Ontologies -- Emotional Cognitive Agents with Adaptive Ontologies -- Viral Knowledge Acquisition Through Social Networks --
|
| 653 |
|
|
|a Computer Communication Networks
|
| 653 |
|
|
|a Information Storage and Retrieval
|
| 653 |
|
|
|a Artificial Intelligence
|
| 653 |
|
|
|a Database Management
|
| 653 |
|
|
|a Application software
|
| 653 |
|
|
|a Information storage and retrieval systems
|
| 653 |
|
|
|a Computer networks
|
| 653 |
|
|
|a Artificial intelligence
|
| 653 |
|
|
|a Computer and Information Systems Applications
|
| 653 |
|
|
|a Database management
|
| 700 |
1 |
|
|a Zhang, Chengqi
|e [editor]
|
| 700 |
1 |
|
|a Skormin, Victor
|e [editor]
|
| 700 |
1 |
|
|a Cao, Longbing
|e [editor]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b Springer
|a Springer eBooks 2005-
|
| 490 |
0 |
|
|a Lecture Notes in Artificial Intelligence
|
| 028 |
5 |
0 |
|a 10.1007/978-3-540-72839-9
|
| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-540-72839-9?nosfx=y
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 006.3
|
| 520 |
|
|
|a Since early 1990, multi-agent systems (MAS), data mining, and knowledge d- covery (KDD) have remained areas of high interest in the research and - velopment of intelligent information technologies. Indeed, MAS o?ers powerful metaphors for information system conceptualization, a range of new techniques, and technologies speci?cally focused on the design and implementation of lar- scale open distributed intelligent systems. KDD also provides intelligent inf- mation technology with powerful ideas, algorithms, and software means to help cope with the main problem of arti?cial intelligence, formulated in the we- known question “Where does the knowledge come from?”, thus actually making modern applications intelligent and adaptive. The evident recent trend in both science and industry is to integrate and take advantage of both technologies. The existing experience with combined application of multi-agent technology to design architectures of distributed (- erarchical and peer-to-peer) data mining and KDD systems, as well as the u- lization of data mining and KDD achievements to provide enhanced intelligence of MAS, con?rms the fact that both technologies are capable of mutual enri- ment and their integrateduse may result in intelligent information systems with new emergent properties. The 1st International Workshop “Autonomous Int- ligent Systems: Agents and Data Mining” (AIS-ADM 2005, June 6–8, 2005, St. Petersburg, Russia) was a response to the aforementioned trend. It con?rmed the interest of academic and industry communities in advancing the e?orts to integrate achievements in MAS and KDD, thus resulting in a new dimension and further progress in intelligent information technology
|