Abstract
Mining of association rules is of interest to data miners. Typically, before association rules are mined, a user needs to determine a support threshold in order to obtain only the frequent item sets. Having users to determine a support threshold attracts a number of issues. We propose an association rule mining framework that does not require a pre-set support threshold. The framework is developed based on implication of propositional logic. The experiments show that our approach is able to identify meaningful association rules.
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- 1.
Both inverse and contrapositive have the same number of co-occurrences in transaction records.
- 2.
We write the union of item sets X and E (X ∪ E) as XE.
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Sim, A.T.H., Zutshi, S., Indrawan, M., Srinivasan, B. (2009). Discovering Knowledge of Association Using Coherent Rules. In: Wai, PK., Huang, X., Ao, SI. (eds) Trends in Communication Technologies and Engineering Science. Lecture Notes in Electrical Engineering, vol 33. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9532-0_24
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DOI: https://doi.org/10.1007/978-1-4020-9532-0_24
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