Journal
DECISION SUPPORT SYSTEMS
Volume 42, Issue 2, Pages 859-878Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.dss.2005.07.009
Keywords
data warehouse; data mining; association rules; dimensional model; database systems; knowledge discovery
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Data warehouses store data that explicitly and implicitly reflect customer patterns and trends, financial and business practices, strategies, know-how, and other valuable managerial information. In this paper, we suggest a novel way of acquiring more knowledge from corporate data warehouses. Association-rule mining, which captures co-occurrence patterns within data, has attracted considerable efforts from data warehousing researchers and practitioners alike. In this paper, we present a new data-mining method called qualified association rules. Qualified association rules capture correlations across the entire data warehouse, not just over an extracted and transformed portion of the data that is required when a standard datamining tool is used. (c) 2005 Elsevier B.V. All rights reserved.
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