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Frequent Itemsets Mining for Book Renting System By Using FP-Growth

http://hdl.handle.net/20.500.12678/0000003421
acbb9be7-ae1d-451c-bc45-4088997cbb90
7b849983-3560-466d-ba01-464bdb2400b6
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psc2010paper psc2010paper (227).pdf (442 Kb)
Publication type
Article
Upload type
Publication
Title
Title Frequent Itemsets Mining for Book Renting System By Using FP-Growth
Language en
Publication date 2010-12-16
Authors
Tun, Sandar
Description
Frequent itemsets mining leads to the discovery of associations and correlations among items in large transactional or relational data sets. Frequent itemsets mining is market basket analysis. This paper presents to analyzes books renting habits by finding associations between the different items that borrowers place in their shopping (renting) baskets. In the proposed system, FP-growth (Frequent Pattern growth) is used to find the frequent itemsets without candidate generation. FP-growth is an order of magnitude faster than Apriori for no candidate generation, no candidate test, the use compact data structure, the elimination of repeated database scan and that basic operation is counting and FP-tree building.
Keywords
Data mining, Association Rule, FP-Growth
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/1174
Journal articles
Fifth Local Conference on Parallel and Soft Computing
Conference papers
Books/reports/chapters
Thesis/dissertations
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