Data Warehousing and Knowledge Discovery
Springer Berlin (Verlag)
978-3-540-37736-8 (ISBN)
ETL Processing.- ETLDiff: A Semi-automatic Framework for Regression Test of ETL Software.- Applying Transformations to Model Driven Data Warehouses.- Bulk Loading a Linear Hash File.- Materialized View.- Dynamic View Selection for OLAP.- Preview: Optimizing View Materialization Cost in Spatial Data Warehouses.- Preprocessing for Fast Refreshing Materialized Views in DB2.- Multidimensional Design.- A Multiversion-Based Multidimensional Model.- Towards Multidimensional Requirement Design.- Multidimensional Design by Examples.- OLAP and Multidimensional Model.- Extending Visual OLAP for Handling Irregular Dimensional Hierarchies.- A Hierarchy-Driven Compression Technique for Advanced OLAP Visualization of Multidimensional Data Cubes.- Analysing Multi-dimensional Data Across Autonomous Data Warehouses.- What Time Is It in the Data Warehouse?.- Cubes Processing.- Computing Iceberg Quotient Cubes with Bounding.- An Effective Algorithm to Extract Dense Sub-cubes from a Large Sparse Cube.- On the Computation of Maximal-Correlated Cuboids Cells.- Data Warehouse Applications.- Warehousing Dynamic XML Documents.- Integrating Different Grain Levels in a Medical Data Warehouse Federation.- A Versioning Management Model for Ontology-Based Data Warehouses.- Data Warehouses in Grids with High QoS.- Mining Techniques (1).- Mining Direct Marketing Data by Ensembles of Weak Learners and Rough Set Methods.- Efficient Mining of Dissociation Rules.- Optimized Rule Mining Through a Unified Framework for Interestingness Measures.- An Information-Theoretic Framework for Process Structure and Data Mining.- Mining Techniques (2).- Mixed Decision Trees: An Evolutionary Approach.- ITER: An Algorithm for Predictive Regression Rule Extraction.- COBRA: Closed Sequential Pattern Mining Using Bi-phase Reduction Approach.- Frequent Itemsets.- A Greedy Approach to Concurrent Processing of Frequent Itemset Queries.- Two New Techniques for Hiding Sensitive Itemsets and Their Empirical Evaluation.- EStream: Online Mining of Frequent Sets with Precise Error Guarantee.- Mining Data Streams.- Granularity Adaptive Density Estimation and on Demand Clustering of Concept-Drifting Data Streams.- Classification of Hidden Network Streams.- Adaptive Load Shedding for Mining Frequent Patterns from Data Streams.- An Approximate Approach for Mining Recently Frequent Itemsets from Data Streams.- Ontology-Based Mining.- Learning Classifiers from Distributed, Ontology-Extended Data Sources.- A Coherent Biomedical Literature Clustering and Summarization Approach Through Ontology-Enriched Graphical Representations.- Automatic Extraction for Creating a Lexical Repository of Abbreviations in the Biomedical Literature.- Clustering.- Priority-Based k-Anonymity Accomplished by Weighted Generalisation Structures.- Achieving k-Anonymity by Clustering in Attribute Hierarchical Structures.- Calculation of Density-Based Clustering Parameters Supported with Distributed Processing.- Cluster-Based Sampling Approaches to Imbalanced Data Distributions.- Advanced Mining Techniques.- Efficient Mining of Large Maximal Bicliques.- Automatic Image Annotation by Mining the Web.- Privacy Preserving Spatio-Temporal Clustering on Horizontally Partitioned Data.- Association Rules.- Discovering Semantic Sibling Associations from Web Documents with XTREEM-SP.- Difference Detection Between Two Contrast Sets.- EGEA : A New Hybrid Approach Towards Extracting Reduced Generic Association Rule Set (Application to AML Blood Cancer Therapy).- Miscellaneous Applications.- AISS: An Index for Non-timestamped Set Subsequence Queries.- A Method for Feature Selection on Microarray Data Using Support Vector Machine.- Providing Persistence for Sensor Data Streams by Remote WAL.- Classification.- Support Vector Machine Approach for Fast Classification.- Document Representations for Classification of Short Web-Page Descriptions.- GARC: A New Associative Classification Approach.- Conceptual Modeling for Classification Mining in Data Warehouses.
Erscheint lt. Verlag | 30.8.2006 |
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Reihe/Serie | Information Systems and Applications, incl. Internet/Web, and HCI | Lecture Notes in Computer Science |
Zusatzinfo | XVIII, 582 p. |
Verlagsort | Berlin |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 1840 g |
Themenwelt | Informatik ► Theorie / Studium ► Algorithmen |
Schlagworte | classification • Clustering • data cubes • data engineering • Data Management • Data Mining • Data Semantics • data stream mining • Data Warehouse • Data Warehouses • Data Warehousing • ETL processing • Knowledge Discovery • LA • OLAP • On-Line Analytical Processing • Ontologies • Ontology • pattern mining • privacy • query processing • service-oriented computing • Warehousing • XML |
ISBN-10 | 3-540-37736-0 / 3540377360 |
ISBN-13 | 978-3-540-37736-8 / 9783540377368 |
Zustand | Neuware |
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