Maintenance of generalized association rules for record deletion based on the pre-large concept
Tzung‐Pei Hong, Tzu‐Jung Huang · 2007
Abstract:- In the past, we proposed an incremental mining algorithm for maintenance of generalized association rules as new transactions were inserted. Deletion of records in databases is, however, commonly seen in real-world applications. In this paper, we thus attempt to extend our previous approach to solve this issue. The proposed algorithm maintains generalized association rules based on the concept of pre-large itemsets for deleted data. The concept of pre-large itemsets is used to reduce the need for rescanning original databases and to save maintenance costs. The proposed algorithm doesn't need to rescan the original database until a number of records have been deleted. It can thus save much maintenance time. Key-Words:- data mining, generalized association rule, taxonomy, large itemset, pre-large itemset. 1