Comprehensive data warehouse exploration with qualified association-rule mining [An article from: Decision Support Systems]

This digital document is a journal article from Decision Support Systems, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
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 data-mining tool is used.