Data Warehousing and Knowledge Discovery : 5th International Conference, DaWaK 2003, Prague, Czech Republic, September 3-5,2003, Proceedings / edited by Yahiko Kambayashi, Mukesh Mohania, Wolfram Wöß.

Format:

Book

Contributor:

Kambayashi, Y., editor.

Mohania, Mukesh, editor.

Wöss, Wolfram, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science 0302-9743 ; 2737.

Lecture Notes in Computer Science, 0302-9743 ; 2737

Language:

English

Subjects (All):

Computer science.

Computer Science, general.

Local Subjects:

Computer Science, general.

Physical Description:

1 online resource (XIV, 438 pages).

Edition:

First edition 2003.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2003.

System Details:

text file PDF

Summary:

This book constitutes the refereed proceedings of the 5th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2003, held in Prague, Czech Republic in September 2003. The 41 revised full papers presented were carefully reviewed and selected from more than 130 submissions. The papers are organized in topical sections on data cubes and queries, multidimensional data models, Web warehousing, change detection, Web mining and association rules, association rules and decision trees, clustering, association rule mining, data analysis and discovery, ontologies and improving data quality, queries and data patterns, improving database query engines, and sampling and vector classification.

Contents:

Invited Talk

XML for Data Warehousing Chances and Challenges

Data Cubes and Queries

CPM: A Cube Presentation Model for OLAP

Computation of Sparse Data Cubes with Constraints

Answering Joint Queries from Multiple Aggregate OLAP Databases

An Approach to Enabling Spatial OLAP by Aggregating on Spatial Hierarchy

Multidimensional Data Model

A Multidimensional Aggregation Object (MAO) Framework for Computing Distributive Aggregations

The GMD Data Model for Multidimensional Information: A Brief Introduction

An Application of Case-Based Reasoning in Multidimensional Database Architecture

Web Warehousing

MetaCube XTM: A Multidimensional Metadata Approach for Semantic Web Warehousing Systems

Designing Web Warehouses from XML Schemas

Building XML Data Warehouse Based on Frequent Patterns in User Queries

Change Detection

A Temporal Study of Data Sources to Load a Corporate Data Warehouse

Automatic Detection of Structural Changes in Data Warehouses

Performance Tests in Data Warehousing ETLM Process for Detection of Changes in Data Origin

Web Mining and Association Rule

Recent Developments in Web Usage Mining Research

Parallel Vector Computing Technique for Discovering Communities on the Very Large Scale Web Graph

Association Rules and Decision Trees

Ordinal Association Rules towards Association Rules

Rough Set Based Decision Tree Model for Classification

Inference Based Classifier: Efficient Construction of Decision Trees for Sparse Categorical Attributes

Generating Effective Classifiers with Supervised Learning of Genetic Programming

Clustering I

Clustering by Regression Analysis

Handling Large Workloads by Profiling and Clustering

Incremental OPTICS: Efficient Computation of Updates in a Hierarchical Cluster Ordering

Clustering II

On Complementarity of Cluster and Outlier Detection Schemes

Cluster Validity Using Support Vector Machines

FSSM: Fast Construction of the Optimized Segment Support Map

Association Rule Mining

Using a Connectionist Approach for Enhancing Domain Ontologies: Self-Organizing Word Category Maps Revisited

Parameterless Data Compression and Noise Filtering Using Association Rule Mining

Performance Evaluation of SQL-OR Variants for Association Rule Mining

Data Analysis and Discovery

A Distance-Based Approach to Find Interesting Patterns

Similarity Search in Structured Data

Ontologies and Improving Data Quality

Using an Interest Ontology for Improved Support in Rule Mining

Fraud Formalization and Detection

Combining Noise Correction with Feature Selection

Queries and Data Patterns

Pre-computing Approximate Hierarchical Range Queries in a Tree-Like Histogram

Comprehensive Log Compression with Frequent Patterns

Non-recursive Generation of Frequent K-itemsets from Frequent Pattern Tree Representations

Improving Database Query Engine

A New Computation Model for Rough Set Theory Based on Database Systems

Computing SQL Queries with Boolean Aggregates

Fighting Redundancy in SQL

Sampling and Vector Classification

"On-the-fly" VS Materialized Sampling and Heuristics

Incremental and Decremental Proximal Support Vector Classification using Decay Coefficients.

Other Format:

Printed edition:

ISBN:

978-3-540-45228-7

9783540452287

Access Restriction:

Restricted for use by site license.