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CiteWeb id: 19930000007

CiteWeb score: 18765

DOI: 10.1145/170035.170072

We are given a large database of customer transactions. Each transaction consists of items purchased by a customer in a visit. We present an efficient algorithm that generates all significant association rules between items in the database. The algorithm incorporates buffer management and novel estimation and pruning techniques. We also present results of applying this algorithm to sales data obtained from a large retailing company, which shows the effectiveness of the algorithm.

The publication "Mining association rules between sets of items in large databases" is placed in the Top 1000 of the best publications in CiteWeb. Also in the category Computer Science it is included to the Top 100. Additionally, the publicaiton "Mining association rules between sets of items in large databases" is placed in the Top 100 among other scientific works published in 1993.
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