Algorithms for mining association rules in bag databases

Ping Yu Hsu, Yen Liang Chen, Chun Ching Ling

研究成果: 雜誌貢獻期刊論文同行評審

53 引文 斯高帕斯(Scopus)

摘要

Existing studies in mining association rules in transaction databases assume that a transaction only records the items bought in that particular transaction. However, a typical transaction also records the quantities of items. Because quantity information is not incorporated in the analysis, the association rules cannot reveal what quantities of different items are related with one another. Therefore, this paper reconsiders the conventional transaction database by assuming that each transaction is formed of a set of items as well as their quantities. (We name this extended transaction database as bag database.) In bag databases, algorithms are developed for mining association rules including items' quantities, and three kinds of association rules are generated.

原文???core.languages.en_GB???
頁(從 - 到)31-47
頁數17
期刊Information Sciences
166
發行號1-4
DOIs
出版狀態已出版 - 29 10月 2004

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