Generate Efficient Rule Flow with Expert Knowledge
Original Publication Date: 2009-Apr-21
Included in the Prior Art Database: 2009-Apr-21
We present a method to generate efficient rule flow with expert knowledge. For rule execution, condition re-evaluations induce the main computation cost from condition evaluation. However, some known knowledge, such as non-dependency between two rules, can help to improve the execution efficiency because the re-evaluation for a specific rule is not necessary if the non-dependency between the executed rule and this specific rule is known. We define rule flow as a directed graph while rules are arranged on the nodes and the directed edges indicate the evaluation orders. First, we generate the complete graph from priority based rule execution algorithm. Then, we propose methods to automatically prune the graph with the given expert knowledge. At last, some nodes are combined to simplify the rule flow. Experiments indicate that our approach can generate an efficient rule flow which has the higher execution efficiency than the priority based rule execution algorithm.