β Scribed by Daniel Fasel (auth.)
No coin nor oath required. For personal study only.
The numeric values retrieved from a data warehouse may be difficult for business users to interpret, and may even be interpreted incorrectly. Therefore, in order to better βunderstand numeric values, business users may require an interpretation in meaningful, non-numeric terms. However, if the transition between non-numeric terms is crisp, true values cannot be measured and a smooth transition between classes may no longer be possible. This book addresses this problem by presenting a fuzzy classification-based approach for a data warehouses. Moreover, it introduces a modeling approach for fuzzy data warehouses that makes it possible to integrate fuzzy linguistic variables in a meta-table structure. The essence of this structure is that fuzzy concepts can be integrated into the dimensions and facts of an existing classical data warehouse without affecting its core. This allows a simultaneous analysis, both fuzzy and crisp. A case study of a movie rental company underlines and exemplifies the proposed approach.
Front Matter....Pages i-xxiv
Introduction....Pages 1-8
Front Matter....Pages 9-9
Fundamental Concepts....Pages 11-42
Fuzzy Data Warehouse....Pages 43-114
Front Matter....Pages 115-115
Application of Fuzzy Data Warehouse....Pages 117-150
Front Matter....Pages 151-151
Implementation of Fuzzy Data Warehouse....Pages 153-182
Front Matter....Pages 183-183
Evaluation and Conclusion of Fuzzy Data Warehouse....Pages 185-193
Back Matter....Pages 195-236
Business Information Systems; Information Systems and Communication Service; Data Mining and Knowledge Discovery
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