Publication Details

AprioriItemset - A New Algorithm for Discovering Frequent Itemsets

KOTÁSEK, P.; ZENDULKA, J. AprioriItemset - A New Algorithm for Discovering Frequent Itemsets. 33rd Spring International Conference Modelling and Simulation of Systems MOSIS'99 Proceedings ISM'99 Information Systems Modelling. Rožnov pod Radhoštěm: 1999. p. 49-56. ISBN: 80-85988-31-3.
Type
conference paper
Language
English
Authors
Kotásek Petr, Ing.
Zendulka Jaroslav, doc. Ing., CSc. (UIFS)
Keywords

association rule, support, confidence, strong rules, itemset, frequent itemset, k-itemset

Abstract

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.

Annotation

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.

Published
1999
Pages
49–56
Proceedings
33rd Spring International Conference Modelling and Simulation of Systems MOSIS'99 Proceedings ISM'99 Information Systems Modelling
ISBN
80-85988-31-3
Place
Rožnov pod Radhoštěm
BibTeX 
@inproceedings{BUT191384,
  author="Petr {Kotásek} and Jaroslav {Zendulka}",
  title="AprioriItemset - A New Algorithm for Discovering Frequent Itemsets",
  booktitle="33rd Spring International Conference Modelling and Simulation of Systems MOSIS'99 Proceedings ISM'99 Information Systems Modelling",
  year="1999",
  pages="49--56",
  address="Rožnov pod Radhoštěm",
  isbn="80-85988-31-3"
}
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