Mining Association Rules in Large Database by Implementing Pipelining Technique in Partition Algorithm | Zendy

Kanhaiya Lal | Zendy; N. C. Mahanti | Zendy

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Mining Association Rules in Large Database by Implementing Pipelining Technique in Partition Algorithm

Author(s) -

Kanhaiya Lal,

N. C. Mahanti

Publication year - 2010

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/657-924

Subject(s) - computer science , partition (number theory) , association rule learning , data mining , algorithm , parallel computing , mathematics , combinatorics

Mining for association rules between items in a large database of sales transactions has been described as an important database mining problem. In this paper we present an efficient algorithm for mining association rules that is faster than the previously proposed partition algorithms approximately m times where m is the number of stages in pipeline. The algorithm is also ideally suited for parallelization. General Terms Database, Data Mining, Algorithms

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