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2000
Springer

Calculating a New Data Mining Algorithm for Market Basket Analysis

11 years 11 months ago
Calculating a New Data Mining Algorithm for Market Basket Analysis
The general goal of data mining is to extract interesting correlated information from large collection of data. A key computationally-intensive subproblem of data mining involves finding frequent sets in order to help mine association rules for market basket analysis. Given a bag of sets and a probability, the frequent set problem is to determine which subsets occur in the bag with some minimum probability. This paper provides a convincing application of program calculation in the derivation of a new and fast algorithm for this practical problem. Beginning with a simple but inefficient specification expressed in a functional language, the new algorithm is calculated in a systematic manner from the specification by applying a sequence of known calculation techniques.
Zhenjiang Hu, Wei-Ngan Chin, Masato Takeichi
Added 25 Aug 2010
Updated 25 Aug 2010
Type Conference
Year 2000
Where PADL
Authors Zhenjiang Hu, Wei-Ngan Chin, Masato Takeichi
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