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CBR for Advice Giving in a Data-Intensive Environment
 

Summary: CBR for Advice Giving
in a Data-Intensive Environment
Agnar AAMODT
Volve AS, Trondheim, Norway
Abstract. Reusing past experiences by reasoning from past cases poses particular
problems when the input to case retrieval comes from large amounts of online data.
Volve has developed a system in which data from oil well drilling logs are continuously
monitored, interpreted, and used to check if previous incidents exist that may predict an
unwanted event to happen unless preventive actions are taken. The system is currently
being tested.
Keywords. case-based reasoning, decision support, online data analysis, oil-well drilling
Invited talk summary paper.
Introduction
Reusing past experience, i.e. being reminded of similar situations and making use of
decision steps made earlier, has turned out to be an efficient way to handle new situations
for human beings. Case-Based Reasoning (CBR) builds upon this principle in order to
provide improved computer-assistance to people in their daily work. As CBR is becoming
more utilized for experience capture and reuse in real-world industrial settings (e.g. [1]),
methods for linking human experiences to the observed data related to those experiences are
getting increased attention. Many industries, including the oil & gas industry, have access to

  

Source: Aamodt, Agnar - Department of Computer and Information Science, Norwegian University of Science and Technology

 

Collections: Computer Technologies and Information Sciences