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Greetings: Broadly speaking, my interests are formal language theory and backtracking as they relate to event correlation engines for enterprise fault monitoring tools. Popular correlation methodologies in the software industry today are state-based, circuit-based and codebook-based (expert systems). However, I'd be more interested in the dynamic instantiation of inference rules and mapping those rules onto the event stream to make predictions about the future. For true proactive fault monitoring would require an expert system that learns over time on its own, based on the enterprise in which it is installed, to make predictions with varying levels of confidence and acting upon them accordingly. In fact, this is something the IBM® Research - Computer Science Lab is already working on right now! One project focuses on machine-learning approaches to developing Self-Aware distributed systems by using real-time Bayesian inference and learning combined with information-theoretic methods for optimal test selection. Peter Drucker, expert in the worlds of business and academia, regarded as the founding father of the study of management, once said that the fewer data needed, the better the information. Complex Event Processing (CEP) is about that, but in real time.
In closing, I'd like to leave you with some advice that will enhance your success, sanity and happiness: Best Regards, |
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