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Mining association rules between sets of items in large databases

Rakesh Agrawal; Tomasz Imieliński; Arun Swami · OpenAlex · 1993

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Author / responsible party
Rakesh Agrawal; Tomasz Imieliński; Arun Swami
Publisher
OpenAlex
Year
1993
Language
English

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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.

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APA 7

Agrawal, R, Imieliński, T, & Swami, A. (1993). Mining association rules between sets of items in large databases. https://doi.org/10.1145/170035.170072

MLA

Agrawal, Rakesh, et al. "Mining association rules between sets of items in large databases." 1993. https://doi.org/10.1145/170035.170072.

Chicago

Agrawal, Rakesh, Tomasz Imieliński, and Arun Swami. 1993. "Mining association rules between sets of items in large databases.". https://doi.org/10.1145/170035.170072.

Harvard

Agrawal, R, Imieliński, T. and Swami, A. 1993, Mining association rules between sets of items in large databases, OpenAlex, available at: https://doi.org/10.1145/170035.170072 [Accessed 6 Aug. 2026].

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Resource details

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Title
Mining association rules between sets of items in large databases
Author / contributors
Rakesh Agrawal; Tomasz Imieliński; Arun Swami
Publisher
OpenAlex
Publication year
1993
Language
English

Subjects

Explore related resources through these subjects.

Association rule learning; Database transaction; Computer science; Pruning; Database; Data mining; Apriori algorithm; Transaction data; Data warehouse; Association (psychology); Affinity analysis; Transaction processing
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