Integrating User's Domain Knowledge with Association Rule Mining
This paper presents a variation of Apriori algorithm that
includes the role of domain expert to guide and speed up the
overall knowledge discovery task. Usually, the user is
interested in finding relationships between certain attributes
instead of the whole dataset. Moreover, he can help the mining
algorithm to select the target database which in turn takes less
time to find the desired association rules. Variants of the
standard Apriori and Interactive Apriori algorithms have been
run on artificial datasets. The results show that incorporating
user's preference in selection of target attribute helps to search
the association rules efficiently both in terms of space and time.
Keywords: Domain, association rule, data mining, Apriori,
interactive Apriori
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