A Semantic-Oriented Framework for System Diagnosis
In the field of system and network diagnosis, there is a variety of modeling and inference methods reported in literature. However, very few are focusing on the validation and knowledge transfer in case of similar symptoms. Many researchers targeted the use of a generic diagnosis framework, semantic-oriented solutions, and temporal aspects related to diagnosis validation. Event correlation and action triggering are essential for an accurate diagnosis decision. However, no industry-wide solution was considered so far. In this paper, the authors are proposing an adaptive framework for diagnosis validation and transfer of information from successful outcomes for future use and optimization of the diagnostic activity. It is shown that this mechanism allows a post-validation of successful diagnosis actions, optimizing the diagnosis process and increasing its accuracy.