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Mining dense data: Association rule discovery on benchmark case study
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نویسنده
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wan abu bakar w.a. ,md. saman m.y. ,abdullah z. ,abd jalil m.m. ,herawan t.
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منبع
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jurnal teknologi - 2016 - دوره : 78 - شماره : 2-2 - صفحه:131 -135
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چکیده
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Data mining (dm),is the process of discovering knowledge and previously unknown pattern from large amount of data. the association rule mining has been in trend where a new pattern analysis can be discovered to project for an important prediction about any issues. in this article,we present comparison result between apriori and fp-growth algorithm in generating association rules based on a benchmark data from frequent itemset mining data repository. experimentation with the two (2) algorithms are done in rapid miner 5.3.007 and the performance result is shown as a comparison. the results obtained confirmed and verified the results from the previous works done. © 2016 penerbit utm press. all rights reserved.
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کلیدواژه
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Association Rule Mining (ARM); Data Mining (DM); Frequent itemset; Interestingness measure; Rapid Miner (RM)
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آدرس
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school of informatics and applied mathematics,universiti malaysia terengganu,kuala terengganu,terengganu, Malaysia, school of informatics and applied mathematics,universiti malaysia terengganu,kuala terengganu,terengganu, Malaysia, school of informatics and applied mathematics,universiti malaysia terengganu,kuala terengganu,terengganu, Malaysia, school of informatics and applied mathematics,universiti malaysia terengganu,kuala terengganu,terengganu, Malaysia, department of information systems,faculty of computer science and information technology,university of malaya,lembah pantai,kuala lumpur, Malaysia
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Authors
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