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International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 12    
Website: http://www.ijser.org
scirp IJSER >> Volume 2, Issue 12, December 2011
Mining Frequent Item Sets from incremental database : A single pass approach
Full Text(PDF, 3000)  PP.  
Author(s)
Sandhya Rani Jetti, Sujatha D
KEYWORDS
Apriori;Association Rules;Vertical format ;data mining; Frequent itemsets mining; Vertical data layout; Algorithm
ABSTRACT
Apriori based Association Rule Mining (ARM) is one of the data mining techniques used to extract hidden knowledge from datasets that can be used by an organization's decision makers to improve overall profit. Performing Existing association mining algorithms requires repeated passes over the entire database. Obviously, for large database, the role of input/output overhead in scanning the database is very significant. We propose a new algorithm, which would mine frequent item sets with vertical format. The new algorithm would need to scan database one time. And in the follow-up data mining process, it can get new frequent item sets through 'and operation' between item sets. The new algorithm needs less storage space, and can improve the efficiency of data mining
References
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