A collaborative distributed privacy-sensitive decision support system for monitoring heterogeneous data sources

被引:0
|
作者
Kargupta, H [1 ]
Sarkar, K [1 ]
Aswath, D [1 ]
Handy, WD [1 ]
机构
[1] AGNIK LLC, Columbia, MD 21045 USA
关键词
data stream; decision support; data mining; collaborative technologies; threat detection;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper introduces MCDS, a Multi-organizational Collaborative Decision Support system that makes an effort to support seamless integration of humans and software agents for collaborative emergency preparedness and threat management in a distributed multi-party environment with heterogeneous social and organizational cultures. MCDS offers mechanisms,for syslematic defection, tracking, and management of emerging threat-structures in the context of the existing assets, algorithms for mining distributed multi-party data in a privacy-sensitive manner, archival and retrieval of case histories, and relevance feedback-based personalization. The paper provides an overview of a few modules and describes two ongoing applications of this collaborative problem solving technology.
引用
收藏
页码:380 / 387
页数:8
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