Mining Association Rules between Sets of Items in Large Databases

Mining Association Rules between Sets of Items in Large Databases (1993)

by Rakesh Agrawal , Tomasz Imielinski , Arun Swami

Venue:	IN: PROCEEDINGS OF THE 1993 ACM SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, WASHINGTON DC (USA
Citations:	1953 - 15 self

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Datum	Value	Source
TITLE	Mining Association Rules between Sets of Items in Large Databases	SVM HeaderParse 0.2
AUTHOR NAME	Rakesh Agrawal	user correction
AUTHOR AFFIL	IBM Almaden Research Center	user correction
AUTHOR ADDR	650 Harry Road, San Jose, CA 95120	user correction
AUTHOR NAME	Tomasz Imielinski	user correction
AUTHOR AFFIL	IBM Almaden Research Center	user correction
AUTHOR ADDR	650 Harry Road, San Jose, CA 95120	user correction
AUTHOR NAME	Arun Swami	user correction
AUTHOR AFFIL	IBM Almaden Research Center	user correction
AUTHOR ADDR	650 Harry Road, San Jose, CA 95120	user correction
ABSTRACT	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.	user correction
YEAR	1993	INFERENCE
VENUE	IN: PROCEEDINGS OF THE 1993 ACM SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, WASHINGTON DC (USA	user correction
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	207--216	INFERENCE
CITATIONS	13 found	ParsCit 1.0