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Title:
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MINING ASSOCIATION RULES FROM TRANSACTIONAL DATABASES AND APRIORI MULTIPLE ALGORITHM |
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Author(s):
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Predrag Staniić , Savo Tomović |
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ISBN:
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978-972-8924-68-3 |
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Editors:
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Pedro Isaías, Miguel Baptista Nunes and Dirk Ifenthaler |
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Year:
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2008 |
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Edition:
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Single |
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Keywords:
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Data mining, association analysis, Apriori algorithm |
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Type:
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Full Paper |
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First Page:
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227 |
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Last Page:
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234 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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One of the most important data mining problems is mining association rules. In this paper, we consider discovering
association rules from large transactional databases. The problem of discovering association rules can be decomposed
into two subproblems: find large itemsets and generate association rules from large itemsets. The second subproblem is
easier one and the complexity of discovering association rules is determined by complexity of discovering large itemsets.
In this paper, we suggest improvements of the Apriori algorithm, which is one of the most famous algorithms for
discovering large itemsets. Actually, we suggest the original procedure for large itemsets generation, which produce less
number of candidate itemsets and which is efficient than the appropriate procedure of the Apriori algorithm. For its
implementation, we suggest modified sort-merge-join algorithm. Also, we propose a way how to algorithm finishes in
tree database scans. |
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