Decision-Centric Information Monitoring
作者:Len Seligman, Paul Lehner, Ken Smith, Chris Elsaesser, David Mattox
摘要
We are interested in information management for decision support applications, especially those that monitor distributed, heterogeneous databases to assess time-critical decisions. Users of such applications can easily be overwhelmed with data that may change rapidly, may conflict, and may be redundant. Developers are faced with a dilemma: either filter out most information and risk excluding critical items, or gather possibly irrelevant or redundant information, and overwhelm the decision maker. This paper describes a solution to this dilemma called decision-centric information monitoring (DCIM). First, we observe that decision support systems should monitor only information that can potentially change some decision. We present an architecture for DCIM that meets the requirements implied by this observation. We describe techniques for identifying the highest value information to monitor and techniques for monitoring that information despite autonomy, distribution, and heterogeneity of data sources. Finally, we present lessons learned from building LOOKOUT, which is to our knowledge the first implementation of a top-to-bottom system performing decision-centric information monitoring.
论文关键词:information agents, decision support, intelligent situation monitoring, Bayesian networks, data replication
论文评审过程:
论文官网地址:https://doi.org/10.1023/A:1008763603052