Data Warehousing and Knowledge Discovery have been widely accepted as key te- nologies for enterprises and organizations to improve their abilities in data analysis, decision support, and the automatic extraction of knowledge from data. With the exponentially growing amount of information to be included in the decision-making process, the data to be processed become more and more complex in both structure and semantics. Consequently, the process of retrieval and knowledge discovery from this huge amount of heterogeneous complex data constitutes the reality check for research in the area. During the past few years, the International Conference on Data Warehousing and Knowledge Discovery (DaWaK) has become one of the most important international scientific events bringing together researchers, developers and practitioners. The DaWaK conferences served as a prominent forum for discussing latest research issues and experiences in developing and deploying data warehousing and knowledge d- covery systems, applications, and solutions. This year’s conference, the Ninth Inter- tional Conference on Data Warehousing and Knowledge Discovery (DaWaK 2007), built on this tradition of facilitating the cross-disciplinary exchange of ideas, expe- ence and potential research directions. DaWaK 2007 sought to disseminate innovative principles, methods, algorithms and solutions to challenging problems faced in the development of data warehousing, knowledge discovery and data mining applications.
Author(s): Todd Eavis, David Cueva (auth.), Il Yeal Song, Johann Eder, Tho Manh Nguyen (eds.)
Series: Lecture Notes in Computer Science 4654
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2007
Language: English
Pages: 484
Tags: Database Management; Data Mining and Knowledge Discovery; Information Systems Applications (incl.Internet); Computer Communication Networks; Artificial Intelligence (incl. Robotics); Business Information Systems
Front Matter....Pages -
A Hilbert Space Compression Architecture for Data Warehouse Environments....Pages 1-12
Evolution of Data Warehouses’ Optimization: A Workload Perspective....Pages 13-22
What-If Analysis for Data Warehouse Evolution....Pages 23-33
An Extensible Metadata Framework for Data Quality Assessment of Composite Structures....Pages 34-44
Automating the Schema Matching Process for Heterogeneous Data Warehouses....Pages 45-54
A Dynamic View Materialization Scheme for Sequences of Query and Update Statements....Pages 55-65
Spatio-temporal Aggregations in Trajectory Data Warehouses....Pages 66-77
Computing Join Aggregates over Private Tables....Pages 78-88
An Annotation Management System for Multidimensional Databases....Pages 89-98
On the Need of a Reference Algebra for OLAP....Pages 99-110
OLAP Technology for Business Process Intelligence: Challenges and Solutions....Pages 111-122
Built-In Indicators to Automatically Detect Interesting Cells in a Cube....Pages 123-134
Emerging Cubes for Trends Analysis in Olap Databases....Pages 135-144
Domination Mining and Querying....Pages 145-156
Semantic Knowledge Integration to Support Inductive Query Optimization....Pages 157-169
A Clustered Dwarf Structure to Speed Up Queries on Data Cubes....Pages 170-180
An OLAM-Based Framework for Complex Knowledge Pattern Discovery in Distributed-and-Heterogeneous-Data-Sources and Cooperative Information Systems....Pages 181-198
Integrating Clustering Data Mining into the Multidimensional Modeling of Data Warehouses with UML Profiles....Pages 199-208
A UML Profile for Representing Business Object States in a Data Warehouse....Pages 209-220
Selection and Pruning Algorithms for Bitmap Index Selection Problem Using Data Mining....Pages 221-230
MOSAIC: A Proximity Graph Approach for Agglomerative Clustering....Pages 231-240
A Hybrid Particle Swarm Optimization Algorithm for Clustering Analysis....Pages 241-250
Clustering Transactions with an Unbalanced Hierarchical Product Structure....Pages 251-261
Constrained Graph b-Coloring Based Clustering Approach....Pages 262-271
An Efficient Algorithm for Identifying the Most Contributory Substring....Pages 272-282
Mining High Utility Quantitative Association Rules....Pages 283-292
Extraction of Association Rules Based on Literalsets....Pages 293-302
Cost-Sensitive Decision Trees Applied to Medical Data....Pages 303-312
Utilization of Global Ranking Information in Graph- Based Biomedical Literature Clustering....Pages 313-322
Ontology-Based Information Extraction and Information Retrieval in Health Care Domain....Pages 323-333
Fuzzy Classifier Based Feature Reduction for Better Gene Selection....Pages 334-344
Two Way Focused Classification....Pages 345-354
A Markov Blanket Based Strategy to Optimize the Induction of Bayesian Classifiers When Using Conditional Independence Learning Algorithms....Pages 355-364
Learning of Semantic Sibling Group Hierarchies - K-Means vs. Bi-secting-K-Means....Pages 365-374
Mining Top-K Multidimensional Gradients....Pages 375-384
A Novel Similarity-Based Modularity Function for Graph Partitioning....Pages 385-396
Dual Dimensionality Reduction for Efficient Video Similarity Search....Pages 397-406
Privacy-Preserving Genetic Algorithms for Rule Discovery....Pages 407-417
Fast Cryptographic Multi-party Protocols for Computing Boolean Scalar Products with Applications to Privacy-Preserving Association Rule Mining in Vertically Partitioned Data....Pages 418-427
Privacy-Preserving Self-Organizing Map....Pages 428-437
DWFIST: Leveraging Calendar-Based Pattern Mining in Data Streams....Pages 438-448
Expectation Propagation in GenSpace Graphs for Summarization....Pages 449-458
Mining First-Order Temporal Interval Patterns with Regular Expression Constraints....Pages 459-469
Mining Trajectory Patterns Using Hidden Markov Models....Pages 470-480
Back Matter....Pages -
