POST-MINING OF ASSOCIATION RULES USING ONTOLOGIES AND RULE SCHEMAS
2015 ◽
pp. 196-200
Keyword(s):
Knowledge discovery and databases (KDD) deals with the overall process of discovering useful knowledge from data. Data mining is a particular step in this process by applying specific algorithms for extracting hidden fact in the data. Association rule mining is one of the data mining techniques that generate a large number of rules. Several methods have been proposed in the literature to filter and prune the discovered rules to obtain only interesting rules in order to help the decision-maker in a business process. We propose a new approach to integrate user knowledge using ontologies and rule schemas at the stage of post-mining of association rules. General Terms- Lattice, Post-processing, pruning, itemset .
2011 ◽
pp. 307-312
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2010 ◽
pp. 15-32
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2014 ◽
Vol 23
(05)
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pp. 1450004
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2010 ◽
Vol 108-111
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pp. 50-56
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2013 ◽
Vol 765-767
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pp. 282-285
2021 ◽
Vol 23
(2)
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pp. 1137
2011 ◽
pp. 310-326