Agents And Data Mining Interaction

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Agents and Data Mining Interaction

Annotation. This book constitutes the refereed proceedings of the 6th International Workshop on Agents and Data Mining Interaction, ADMI 2010, held in Toronto, Canada, in May 2010. The 15 revised full papers presented were carefully reviewed and selected from 37 submissions. The papers are organized in topical sections on agents for data mining; data mining for agents; data mining in agents; and agent mining applications.
Autonomous Intelligent Systems: Multi-Agents and Data Mining

This book constitutes the refereed proceedings of the Second International Workshop on Autonomous Intelligent Systems: Agents and Data Mining, AIS-ADM 2007, held in St. Petersburg, Russia in June 2007. The 17 revised full papers and six revised short papers presented together with four invited lectures cover agent and data mining, agent competition and data mining, as well as text mining, semantic Web, and agents.
Data Mining and Multi-agent Integration

Author: Longbing Cao
language: en
Publisher: Springer Science & Business Media
Release Date: 2009-07-25
Data Mining and Multi agent Integration aims to re?ect state of the art research and development of agent mining interaction and integration (for short, agent min ing). The book was motivated by increasing interest and work in the agents data min ing, and vice versa. The interaction and integration comes about from the intrinsic challenges faced by agent technology and data mining respectively; for instance, multi agent systems face the problem of enhancing agent learning capability, and avoiding the uncertainty of self organization and intelligence emergence. Data min ing, if integrated into agent systems, can greatly enhance the learning skills of agents, and assist agents with predication of future states, thus initiating follow up action or intervention. The data mining community is now struggling with mining distributed, interactive and heterogeneous data sources. Agents can be used to man age such data sources for data access, monitoring, integration, and pattern merging from the infrastructure, gateway, message passing and pattern delivery perspectives. These two examples illustrate the potential of agent mining in handling challenges in respective communities. There is an excellent opportunity to create innovative, dual agent mining interac tion and integration technology, tools and systems which will deliver results in one new technology.