Consider, a classic example of the following rule:
IF (patient is pregnant) THEN (patient is female).
This rule is very accurate and comprehensible, but it is not interesting, since it represents the obvious.
Another Example from real world data set,
IF (used_seat_belt = ‘yes’) THEN (injury = ‘no’).......................................................(1)
IF ((used_seat_belt = ‘yes’) Λ (passenger = child)) THEN (injury = ‘yes’)...............(2)
Rule (1) is a general and an obvious rule. But rule (2) contradicts the knowledge represented by rule (1) and so the user's belief. This kind of knowledge is unexpected from users preset beliefs and it is always interesting to extract this interesting (or surprising) knowledge from data sets.
“Unexpectedness” means knowledge which is unexpected from the beliefs of users i.e. A decision rule is considered to be interesting (or surprising) if it represents knowledge that was not only previously unknown to the users but also contradicts the original beliefs of the users.
I hope, these examples may help you to understand the concept more clearly.
Yes, firstly, discover the general rules and then discover exceptions to these general rules.
A general rule : If bird then fly
However, there are few exceptional birds like emu and penguin that do not fly. It would definitely be valuable to discover such exceptions along with the rule, making the rule more accurate, comprehensible as well as interesting.