| 書目名稱 | Data Mining and Multi-agent Integration | | 編輯 | Longbing Cao | | 視頻video | http://file.papertrans.cn/263/262941/262941.mp4 | | 概述 | Addresses the merger between two scientific areas: data mining and multi-agents.Includes methodologies, techniques, algorithms, and systems.Real-life applications and systems of multi-agents.Provides | | 圖書封面 |  | | 描述 | 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 e | | 出版日期 | Book 2009 | | 關(guān)鍵詞 | AAMAS; Clustering; agent-enriched data mining; algorithm; algorithms; automated reasoning; classification; | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4419-0522-2 | | isbn_softcover | 978-1-4899-8440-1 | | isbn_ebook | 978-1-4419-0522-2 | | copyright | Springer-Verlag US 2009 |
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