Frequent Itemset Mining Based on Development of FP-growth Algorithm and Use MapReduce Technique
نویسندگان
چکیده
منابع مشابه
Parallelizing Frequent Itemset Mining with FP-Trees
A new scheme to parallelize frequent itemset mining algorithms is proposed. By using the extended conditional databases and k-prefix search space partitioning, our new scheme can create more parallel tasks with better balanced execution times. An implementation of the new scheme with FP-trees is presented. The results of the experimental evaluation showing the increased speedup are presented.
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Discovery of frequent itemsets is a very important data mining problem with numerous applications. Frequent itemset mining is often regarded as advanced querying where a user specifies the source dataset and pattern constraints using a given constraint model. A significant amount of research on frequent itemset mining has been done so far, focusing mainly on developing faster complete mining al...
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ژورنال
عنوان ژورنال: Association of Arab Universities Journal of Engineering Sciences
سال: 2021
ISSN: 2616-9401,1726-4081
DOI: 10.33261/jaaru.2021.28.1.008