Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The rule refinement problem has been known to be one of the most difficult and complex problems.  presents a systematic rule refinement method that deals with the old rule directly with the new data, for the first time. To be able to do the rule refinement, the data are represented in the extended data expression, where an event has its ight of importance. To show how this can be done systematically, a decision tree classifier is used for the rule refinement. The ights of the events of the former rule are adjusted according to the depth of the tree merged with the collected new data set to form the new rule. Experiment shows that this approach, with properly designing the ight assignment procedure, is promising to enhance the performance of the inference engine by generating a rule with higher accuracy than the one from new data set only.
['Jung Min Kong', 'Dong-Hun Seo', 'Won Don Lee']
I am writing a research paper on a idea Rule refinement with extended data expression
[{"from": "human", "value": "I am writing a research paper on a idea Rule refinement with extended data expression"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The rule refinement problem has been known to be one of the most difficult and complex problems.  presents a systematic rule refinement method that deals with the old rule directly with the new data, for the first time. To be able to do the rule refinement, the data are represented in the extended data expression, where an event has its ight of importance. To show how this can be done systematically, a decision tree classifier is used for the rule refinement. The ights of the events of the former rule are adjusted according to the depth of the tree merged with the collected new data set to form the new rule. Experiment shows that this approach, with properly designing the ight assignment procedure, is promising to enhance the performance of the inference engine by generating a rule with higher accuracy than the one from new data set only."}]