Ad-Hoc Association-Rule Mining within the Data Warehouse

Many organizations often underutilize their already constructed data warehouses. In this paper, we suggest a novel way of acquiring more information from corporate data warehouses without the complications and drawbacks of deploying additional software systems. Association-rule mining, which captures co-occurrence patterns within data, has attracted considerable efforts from data warehousing researchers and practitioners alike. Unfortunately, most data mining tools are loosely coupled, at best, with the data warehouse repository. Furthermore, these tools can often find association rules only within the main fact table of the data warehouse (thus ignoring the information-rich dimensions of the star schema) and are not easily applied on non-transaction level data often found in data warehouses. In this paper, we present a new data-mining framework that is tightly integrated with the data warehousing technology. Our framework has several advantages over the use of separate data mining to...

• Type: Conference
• Year: 2003
• Where: HICSS
• Authors: Svetlozar Nestorov, Nenad Jukic
• Keywords: Biometrics, Data Mining, Data Mining Tools, Data Warehouse, HICSS 2003, System Sciences