Dezide White Paper - Capture, Organize and Optimize Expert Knowledge Using Bayesian Belief Networks
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Capturing knowledge in a computer is difficult – making it accessible and useful to others is hard, but it’s exactly in this transformation from tacit to explicit and formalised that we can realise our valuable organizational knowledge and improve efficiency and quality by using it.
This synthesis between human expert knowledge and computers can be enabled by an underlying mathematical model, and if this model is sound, the resulting system can help you fix problems faster and transfer skills easier.
Basically we describe a problem and its solutions using three components:
This paper explains how Dezide uses a mathematical model for capturing and sharing expert troubleshooting knowledge.
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Dezide White Paper
Learn how we utilize the benefits of a sound mathematical model for capturing and optimizing expert troubleshooting knowledge.
CAPTURE TROUBLESHOOTING KNOWLEDGE USING BAYESIAN BELIEF NETWORKS
Capture, Organize and Optimize Expert Knowledge Using Bayesian Belief Networks
Capturing knowledge in a computer is difficult – making it accessible and useful to others is hard, but it’s exactly in this transformation from tacit to explicit and formalised that we can realise our valuable organizational knowledge and improve efficiency and quality by using it.
This paper explains how Dezide uses a mathematical model for capturing and sharing expert troubleshooting knowledge.
Learn how we utilize the benefits of a sound mathematical model for capturing and optimizing expert troubleshooting knowledge.
Learn how we utilize the benefits of a sound mathematical model for capturing and optimizing expert troubleshooting knowledge.