Frequent Itemset Generation for Analyzing Customer Buying Nature using Bit Vector Mining
نویسندگان
چکیده
منابع مشابه
Bit Stream Mask-Search Algorithm in Frequent Itemset Mining
Association Rules in data mining are generated by identifying relationships among set of items in transaction database. Finding frequent itemsets is computationally the most expensive step in Association rule discovery and therefore it has attracted significant research attention. Although several techniques have emerged, they are all inherently dependent on the memory availability. This paper ...
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Mining frequent itemset using bit-vector representation approach is very efficient for small dense datasets, but highly inefficient for sparse datasets due to lack of any efficient bit-vector projection technique. In this paper we present a novel efficient bit-vector projection technique, for sparse and dense datasets. We also present a new frequent itemset mining algorithm Ramp (Real Algorithm...
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Mining frequent itemset using bit-vector representation approach is very efficient for dense type datasets, but highly inefficient for sparse datasets due to lack of any efficient bit-vector projection technique. In this paper we present a novel efficient bit-vector projection technique, for sparse and dense datasets. To check the efficiency of our bit-vector projection technique, we present a ...
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ژورنال
عنوان ژورنال: International Journal for Research in Applied Science and Engineering Technology
سال: 2019
ISSN: 2321-9653
DOI: 10.22214/ijraset.2019.3352