A model-based frequency constraint for mining associations from transaction data

Hahsler, Michael (2004) A model-based frequency constraint for mining associations from transaction data. Working Papers on Information Systems, Information Business and Operations, 07/2004. Institut für Informationsverarbeitung und Informationswirtschaft, WU Vienna University of Economics and Business, Vienna.


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In this paper we develop an alternative to minimum support which utilizes knowledge of the process which generates transaction data and allows for highly skewed frequency distributions. We apply a simple stochastic model (the NB model), which is known for its usefulness to describe item occurrences in transaction data, to develop a frequency constraint. This model-based frequency constraint is used together with a precision threshold to find individual support thresholds for groups of associations. We develop the notion of NB-frequent itemsets and present two mining algorithms which find all NB-frequent itemsets in a database. In experiments with publicly available transaction databases we show that the new constraint can provide significant improvements over a single minimum support threshold and that the precision threshold is easier to use. (author's abstract)

Item Type: Paper
Keywords: data mining / associations / interest measure / mixture models / transaction data
Divisions: Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft
Depositing User: Repository Administrator
Date Deposited: 17 Nov 2004 12:15
Last Modified: 22 Oct 2019 00:41
URI: https://epub.wu.ac.at/id/eprint/1760


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