Self-Learning Expert Systems using Rule Classifier in Detection Engines

摘要

Detection Engines in various applications are either implemented using expert systems or using neural network engines. This paper provides a hybrid approach to combine both systems to give a feedback based self-learning expert system based detection engine. The paper gives details of the approach, framework used and results of some preliminary tests run. It concludes by recommending some extensions to the system that would provide further improvements.