Complex Data Warehousing And Knowledge Discovery For Advanced Retrieval Development
by Tho Manh Nguyen
Recently, researchers have gained innovative principles, methods, algorithms, and solutions to challenging problems faced in the development of data warehousing, knowledge discovery, and data mining applications. Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development: Innovative Methods and Applications provides a comprehensive
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Recently, researchers have gained innovative principles, methods, algorithms, and solutions to challenging problems faced in the development of data warehousing, knowledge discovery, and data mining applications. Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development: Innovative Methods and Applications provides a comprehensive analysis on current issues and trends in retrieval expansion. Containing research from leading international experts, this book presents future challenges and opportunities in the field valuable to academicians, researchers, and practitioners.
Product Details
- ISBN-13:
- 9781605667485
- Publisher:
- IGI Global
- Publication date:
- 02/18/2011
- Series:
- Advances in Data Warehousing and Mining (ADWM) Book Series
- Pages:
- 426
- Product dimensions:
- 8.70(w) x 11.30(h) x 1.20(d)
Table of Contents
Ch. 1 The LBF R-Tree: Scalable Indexing and Storage for Data Warehousing Systems 1
Ch. 2 Dynamic Workload for Schema Evolution in Data Warehouses: A Performance Issue 28
Ch. 3 Preview: Optimizing View Materialization Cost in Spatial Data Warehouses 47
Ch. 4 Decisional Annotations: Integrating and Preserving Decision-Makers' Expertise in Multidimensional Systems 65
Ch. 5 Federated Data Warehouses 82
Ch. 6 Built-In Indicators to Support Business Intelligence in OLAP Databases 108
Ch. 7 Conceptual Data Warehouse Design Methodology for Business Process Intelligence 129
Ch. 8 Data Warehouse Facilitating Evidence-Based Medicine 174
Ch. 9 Deploying Data Warehouses in Grids with Efficiency and Availability 208
Ch. 10 MOSAIC: Agglomerative Clustering with Gabriel Graphs 231
Ch. 11 Ranking Gradients in Multi-Dimensional Spaces 251
Ch. 12 Simultaneous Feature Selection and Tuple Selection for Efficient Classification 270
Ch. 13 Learning Cost-Sensitive Decision Trees to Support Medical Diagnosis 287
Ch. 14 An Approximate Approach for Maintaining Recent Occurrences of Itemsets in a Sliding Window over Data Streams 308
Ch. 15 Protocol Identification of Encrypted Network Streams 328
Ch. 16 Exploring Calendar-Based Pattern Mining in Data Streams 342
Compilation of References 361
Index 400
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