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Association Rule Discovery using TID List Table  

Chai, Duck-Jin (전남대학교 전산학과)
Hwang, Bu-Hyun (전남대학교 전산학과)
Publication Information
Journal of KIISE:Databases / v.32, no.3, 2005 , pp. 219-227 More about this Journal
Abstract
In this paper, we propose an efficient algorithm which generates frequent itemsets by only one database scanning. A frequent itemset is subset of an itemset which is accessed by a transaction. For each item, if informations about transactions accessing the item are exist, it is possible to generate frequent itemsets only by the extraction of items haying an identical transaction ID. Proposed method in this paper generates the data structure which stores transaction ID for each item by only one database scanning and generates 2-frequent itemsets by using the hash technique at the same time. k(k$\geq$3)-frequent itemsets are simply found by comparing previously generated data structure and transaction ID. Proposed algorithm can efficiently generate frequent itemsets by only one database scanning .
Keywords
Data mining; Association rules; Frequent itemsets;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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