Research issues in data stream association rule mining

Authors:
Nan Jiang;Le Gruenwald
Affiliations:
The University of Oklahoma, Norman;The University of Oklahoma, Norman
Venue:
ACM SIGMOD Record
Year:
2006

Citing 31
Cited 55

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Abstract

There exist emerging applications of data streams that require association rule mining, such as network traffic monitoring and web click streams analysis. Different from data in traditional static databases, data streams typically arrive continuously in high speed with huge amount and changing data distribution. This raises new issues that need to be considered when developing association rule mining techniques for stream data. This paper discusses those issues and how they are addressed in the existing literature.