Full Citation

Title: Removing trivial associations in association rule discovery Removing trivial associations in association rule discovery *

Citation Type: Miscellaneous

Publication Year: 2002

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Abstract: Association rule discovery has become one of the most widely applied data mining strategies. Techniques for association rule discovery have been dominated by the frequent itemset strategy as exemplified by the Apriori algorithm. One limitation of this approach is that it provides little opportunity to detect and remove association rules on the basis of relationships between rules. As a result, the association rules discovered are frequently swamped with large numbers of spurious rules that are of little interest to the user. This paper presents association rule discovery techniques that can detect and discard one form of spurious association rule: trivial associations.

Url: https://www.researchgate.net/publication/250187661

User Submitted?: No

Authors: Webb, Geoffrey I; Zhang, Songmao

Publisher: Deakin University

Data Collections: IPUMS USA

Topics: Methodology and Data Collection

Countries: United States