Conference paper

KOTÁSEK Petr and ZENDULKA Jaroslav. AprioriItemset - A New Algorithm for Discovering Frequent Itemsets. In: 33rd Spring International Conference Modelling and Simulation of Systems MOSIS'99 Proceedings ISM'99 Information Systems Modelling. Rožnov pod Radhoštěm, 1999, pp. 49-56. ISBN 80-85988-31-3.
Publication language:english
Original title:AprioriItemset - A New Algorithm for Discovering Frequent Itemsets
Pages:49-56
Proceedings:33rd Spring International Conference Modelling and Simulation of Systems MOSIS'99 Proceedings ISM'99 Information Systems Modelling
Conference:2nd International Workshop Information Systems Modelling - ISM'99
Place:Rožnov pod Radhoštěm, CZ
Year:1999
ISBN:80-85988-31-3
Keywords
association rule, support, confidence, strong rules, itemset, frequent itemset, k-itemset
Annotation
A new algorithm called AprioriItemset for mining association rules is introduced and results of experimental comparison of this algorithm with a well-known algorithm AprioriTid presented.
Abstract
An association rule is a statement of a form "64% of customers who buy nappies also buy beer". The essential point of mining association rules is discovering frequent itemsets. Several algorithms were developed for this purpose. Apriori and AprioriTid algorithms seem to be the best ones so far. We will describe a new algorithm AprioriItemset and present experimental results comparing AprioriTid and AprioriItemset.
BibTeX:
@INPROCEEDINGS{
   author = {Petr Kot{\'{a}}sek and Jaroslav Zendulka},
   title = {AprioriItemset - A New Algorithm for Discovering Frequent
	Itemsets},
   pages = {49--56},
   booktitle = {33rd Spring International Conference Modelling and
	Simulation of Systems MOSIS'99 Proceedings ISM'99
	Information Systems Modelling},
   year = {1999},
   location = {Ro{\v{z}}nov pod Radho{\v{s}}t{\v{e}}m, CZ},
   ISBN = {80-85988-31-3},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php?id=6667}
}

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