Data Warehousing and Knowledge Discovery: First International Conference, DaWaK'99 Florence, Italy, August 30 - September 1, 1999 Proceedings

ISBN-13: 9783540664581 / Angielski / Miękka / 1999 / 408 str.

Mukesh Mohania;A Min Tjoa

Opis

These are the proceedings of the First International Conference on Data Warehousing and Knowledge Discovery, DaWaK'99, held in Florence, Italy in August/September 1999. The book is divided in topical sections on data warehouse design; online analytical processing; view synthesis, selection, and optimization; multidimensional databases; knowledge discovery; association rules; inexing and object similarities; generalized association rules and data and web mining; time series data bases; data mining applications and data analysis.

Spis treści

Data Warehouse Design.- Dynamic Data Warehouse Design.- Star/Snow-Flake Schema Driven Object-Relational Data Warehouse Design and Query Processing Strategies.- The Design and Implementation of Modularized Wrappers/Monitors in a Data Warehouse.- Managing Meta Objects for Design of Warehouse Data.- On-Line Analytical Processing.- Dealing with Complex Reports in OLAP Applications.- OLAP-based Scalable Profiling of Customer Behavior.- Compressed Datacubes for Fast OLAP Applications.- Compact Representation: An Approach to Efficient Implementation for the Data Warehouse Architecture.- View Maintenance, Selection and Optimisation.- On the Independence of Data Warehouse from Databases in Maintaining Join Views.- Heuristic Algorithms for Designing a Data Warehouse with SPJ Views.- POSSE: A Framework for Optimizing Incremental View Maintenance at Data Warehouses.- Genetic Algorithm for Materialized View Selection in Data Warehouse Environments.- Optimization of Sequences of Relational Queries in Decision-Support Environments.- Invited Talk.- Dynamic Data Warehousing.- Multidimensional Databases.- Set-Derivability of Multidimensional Aggregates.- Using the Real Dimension of the Data.- On Schema Evolution in Multidimensional Databases.- Lazy Aggregates for Real-Time OLAP.- Knowledge Discovery.- Incremental Refinement of Mining Queries.- The Item-Set Tree: A Data Structure for Data Mining.- A New Approach for the Discovery of Frequent Itemsets.- K-means Clustering Algorithm for Categorical Attributes.- Association Rules.- Considering Main Memory in Mining Association Rules.- Discovery of Association Rule Meta-Patterns.- Fuzzy Functional Dependencies and Fuzzy Association Rules.- Performance Evaluation and Optimization of Join Queries for Association Rule Mining.- Indexing and Object Similarities.- Efficient Bulk Loading of Large High-Dimensional Indexes.- Implementation of Multidimensional Index Structures for Knowledge Discovery in Relational Databases.- Similarity between Event Types in Sequences.- Generalised Association Rules and Data & Web Mining.- Mining Generalized Association Rule Using Parallel RDB Engine on PC Cluster.- Modeling KDD Processes within the Inductive Database Framework.- Research Issues in Web Data Mining.- DAMISYS: An Overview.- Time Series Databases.- Mining Interval Time Series.- A New Modeling Technique Based on Markov Chains to Mine Behavioral Patterns in Event Based Time Series.- SQL/LPP+: A Cascading Query Language for Temporal Correlation Verification.- Temporal Structures in Data Warehousing.- Data Mining Applications and Data Analysis.- Target Group Selection in Retail Banking through Neuro-Fuzzy Data Mining and Extensive Pre- and Postprocessing.- Using Data Mining Techniques in Fiscal Fraud Detection.- Analysis of Accuracy of Data Reduction Techniques.- Data Swapping: Balancing Privacy against Precision in Mining for Logic Rules.