Szathmary, Laszlo (2018) Finding frequent closed itemsets with an extended version of the Eclat algorithm Annales Mathematicae et Informaticae. 48. pp. 75-82. ISSN 1787-5021 (Print), 1787-6117 (Online)
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Absztrakt (kivonat)
Apriori is the most well-known algorithm for finding frequent itemsets (FIs) in a dataset. For generating interesting association rules, we also need the so-called frequent closed itemsets (FCIs) that form a subset of FIs. Apriori has a simple extension called Apriori-Close that can filter FCIs among FIs. However, it is known that vertical itemset mining algorithms outperform the Apriori-like levelwise algorithms. Eclat is another well-known vertical miner that can produce the same output as Apriori, i.e. it also finds the FIs in a dataset. Here we propose an extension of Eclat, called Eclat-Close that can filter FCIs among FIs. This way Eclat-Close can be used as an alternative of Apriori-Close. Experimental results show that Eclat-Close performs much better than Apriori-Close, especially on dense, highly-correlated datasets.
Mű típusa: | Folyóiratcikk | ||||||||
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Megjegyzés: | Selected papers of the 10th International Conference on Applied Informatics | ||||||||
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Kulcsszavak: | data mining, frequent itemsets, association rules, algorithms | ||||||||
Nyelv: | angol | ||||||||
Kötetszám: | 48. | ||||||||
ISSN: | 1787-5021 (Print), 1787-6117 (Online) | ||||||||
Felhasználó: | Tibor Gál | ||||||||
Dátum: | 13 Már 2019 18:56 | ||||||||
Utolsó módosítás: | 13 Már 2019 18:56 | ||||||||
URI: | http://publikacio.uni-eszterhazy.hu/id/eprint/3315 |
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