Data Warehousing and Knowledge Discovery [electronic resource] : 6th International Conference, DaWaK 2004, Zaragoza, Spain, September 1-3, 2004. Proceedings / edited by Yahiko Kambayashi, Mukesh Mohania, Wolfram Wöß.
Material type: TextSeries: Lecture Notes in Computer Science ; 3181Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2004Description: XIV, 412 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540300762Subject(s): Computer science | Computer Communication Networks | Database management | Information storage and retrieval systems | Information systems | Artificial intelligence | Management information systems | Computer Science | Database Management | Information Storage and Retrieval | Information Systems Applications (incl.Internet) | Computer Communication Networks | Artificial Intelligence (incl. Robotics) | Business Information SystemsAdditional physical formats: Printed edition:: No titleDDC classification: 005.74 LOC classification: QA76.9.D3Online resources: Click here to access onlineCurrent library | Home library | Call number | Materials specified | URL | Status | Date due | Barcode |
---|---|---|---|---|---|---|---|
IMSc Library | IMSc Library | Link to resource | Available | EBK3326 |
Data Warehousing Design -- Conceptual Design of XML Document Warehouses -- Bringing Together Partitioning, Materialized Views and Indexes to Optimize Performance of Relational Data Warehouses -- GeoDWFrame: A Framework for Guiding the Design of Geographical Dimensional Schemas -- Workload-Based Placement and Join Processing in Node-Partitioned Data Warehouses -- Knowledge Discovery Framework and XML Data Minig -- Novelty Framework for Knowledge Discovery in Databases -- Revisiting Generic Bases of Association Rules -- Mining Maximal Frequently Changing Subtree Patterns from XML Documents -- Discovering Pattern-Based Dynamic Structures from Versions of Unordered XML Documents -- Data Cubes and Queries -- Space-Efficient Range-Sum Queries in OLAP -- Answering Approximate Range Aggregate Queries on OLAP Data Cubes with Probabilistic Guarantees -- Computing Complex Iceberg Cubes by Multiway Aggregation and Bounding -- Multidimensional Schema and Data Aggregation -- An Aggregate-Aware Retargeting Algorithm for Multiple Fact Data Warehouses -- A Partial Pre-aggregation Scheme for HOLAP Engines -- Discovering Multidimensional Structure in Relational Data -- Inductive Databases and Temporal Rules -- Inductive Databases as Ranking -- Inductive Databases of Polynomial Equations -- From Temporal Rules to Temporal Meta-rules -- Industrial Track -- How Is BI Used in Industry?: Report from a Knowledge Exchange Network -- Towards an Adaptive Approach for Mining Data Streams in Resource Constrained Environments -- Data Clustering -- Exploring Possible Adverse Drug Reactions by Clustering Event Sequences -- SCLOPE: An Algorithm for Clustering Data Streams of Categorical Attributes -- Novel Clustering Approach that Employs Genetic Algorithm with New Representation Scheme and Multiple Objectives -- Data Visualization and Exploration -- Categorical Data Visualization and Clustering Using Subjective Factors -- Multidimensional Data Visual Exploration by Interactive Information Segments -- Metadata to Support Transformations and Data & Metadata Lineage in a Warehousing Environment -- Data Classification, Extraction and Interpretation -- Classification Based on Attribute Dependency -- OWDEAH: Online Web Data Extraction Based on Access History -- Data Mining Approaches to Diffuse Large B–Cell Lymphoma Gene Expression Data Interpretation -- Data Semantics -- Deriving Multiple Topics to Label Small Document Regions -- Deriving Efficient SQL Sequences via Read-Aheads -- Diversity in Random Subspacing Ensembles -- Association Rule Mining -- Partitioned Approach to Association Rule Mining over Multiple Databases -- A Tree Partitioning Method for Memory Management in Association Rule Mining -- Mining Interesting Association Rules for Prediction in the Software Project Management Area -- Mining Event Sequences -- PROWL: An Efficient Frequent Continuity Mining Algorithm on Event Sequences -- Algorithms for Discovery of Frequent Superset, Rather Than Frequent Subset -- Pattern Mining -- Improving Direct Counting for Frequent Itemset Mining -- Mining Sequential Patterns with Item Constraints -- Mining Borders of the Difference of Two Datacubes -- Mining Periodic Patterns in Sequence Data.
There are no comments on this title.