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What's the difference between size ordering/ data ordering/ least recently used rule?

I did lots of researches already, and most of the books say:

Data ordering: Arrange all possible assertions in one long prioritized list. Use the triggered rule that has condition pattern that matches the highest priority assertion in the list.

Size Ordering: Use the triggered rule with the toughest requirements, where the toughest means the longest list of conditions.

Least recently used rule(Recency Ordering): Use the least recently used rule.

However, all of these explanations are too abstract for me, and I can't understand them well.

Can someone help me using the following cases to explain these three strategies? (Feel free to use own case)

  1. A system to handle complaints quickly. This involves a library of generic excuses whenever a real answer is unavailable.

  2. A system to detect current and prospective clients and forward their calls to appropriate managers.

  3. A sympathizing system to handle complaints. The goal of this system is to have an automated voice have a conversation with the caller and appear knowledgeable and concerned about the complaint. The system wants the caller to end the conversation feeling satisfied that the complaint has been heard and that the company is acting appropriately on it. The system will have a varying amount of information depending on what the caller is willing to say to a machine. The system uses specific rules for when it gathers a lot of information and general rules when it does not.

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