By Katarzyna A. Tarnowska, Zbigniew W. Ras, Pawel J. Jastreboff
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If t is an atomic action term, then t is an action set. 2. If t1 , t2 are action sets, then t1 ∧ t2 is a candidate action set. 3. If t is a candidate action set and for any two atomic actions (a, a1 → a2 ), (b, b1 → b2 ) contained in t we have a = b, then t is an action set. Here b is another attribute (b ∈ A), and b1 , b2 ∈ Vb . 6 By an action rule we mean any expression r = [t1 ⇒ t2 ], where t1 and t2 are action sets. The interpretation of the action rule r is, that by applying the action set t1 , we would get, as a result, the changes of states in action set t2 .
To understand this definition, it is important to introduce some associated concepts, which will be explained later. Action rules can be further improved by the introduction of meta-actions that help control the actions. Meta-actions are mechanism used to acquire knowledge about possible transitions in the information systems and their causes. This knowledge is then used in triggering particular action rules, in order to move objects fromtheir current state to a more desirable state. Meta-actions were first introduced 36 4 Knowledge Discovery Approach for Recommendation to mine actionable patterns, then formally defined and used to discover action rules based on tree classifiers Ras [RD09].
It uses a bottom-up approach to generate action rules having minimal attribute involvement, without the need to find classification rules in the first place. The goal in the algorithm, which is similar to Apriori, is to identify certain relationships between granules, defined by the indiscernibility relation on objects in S. Some of these relationships uniquely define action rules for S. 1. 85. The first step in the procedure is to find pessimistic interpretation in S of all attribute values in V , called granules.