Data Warehousing And Knowledge Discovery: 11th International Conference, Dawak 2009 Linz, Austria, August 31-september 2, 2009 Proceedings (lecture Notes In Computer Science)

This book constitutes the refereed proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery, DaWak 2009 held in Linz, Austria in August/September 2009. The 36 revised full papers presented were carefully reviewed and selected from 124 submissions. The papers are organized in topical sections on data warehouse modeling, data streams, physical design, pattern mining, data cubes, data mining applications, analytics, data mining, clustering, spatio-temporal mining, rule mining, and OLAP recommendation. Front Matter....Pages - New Challenges in Information Integration....Pages 1-8 What Is Spatio-Temporal Data Warehousing?....Pages 9-23 Towards a Modernization Process for Secure Data Warehouses....Pages 24-35 Visual Modelling of Data Warehousing Flows with UML Profiles....Pages 36-47 CAMS: OLAPing Multidimensional Data Streams Efficiently....Pages 48-62 Data Stream Prediction Using Incremental Hidden Markov Models....Pages 63-74 History Guided Low-Cost Change Detection in Streams....Pages 75-86 HOBI: Hierarchically Organized Bitmap Index for Indexing Dimensional Data....Pages 87-98 A Joint Design Approach of Partitioning and Allocation in Parallel Data Warehouses....Pages 99-110 Fast Loads and Fast Queries....Pages 111-124 TidFP: Mining Frequent Patterns in Different Databases with Transaction ID....Pages 125-137 Non-Derivable Item Set and Non-Derivable Literal Set Representations of Patterns Admitting Negation....Pages 138-150 Which Is Better for Frequent Pattern Mining: Approximate Counting or Sampling?....Pages 151-162 A Fast Feature-Based Method to Detect Unusual Patterns in Multidimensional Datasets....Pages 163-176 Efficient Online Aggregates in Dense-Region-Based Data Cube Representations....Pages 177-188 BitCube: A Bottom-Up Cubing Engineering....Pages 189-203 Exact and Approximate Sizes of Convex Datacubes....Pages 204-215 Finding Clothing That Fit through Cluster Analysis and Objective Interestingness Measures....Pages 216-228 Customer Churn Prediction for Broadband Internet Services....Pages 229-243 Mining High-Correlation Association Rules for Inferring Gene Regulation Networks....Pages 244-255 Extend UDF Technology for Integrated Analytics....Pages 256-270 High Performance Analytics with the R 3 -Cache....Pages 271-286 Open Source BI Platforms: A Functional and Architectural Comparison....Pages 287-297 Ontology-Based Exchange and Immediate Application of Business Calculation Definitions for Online Analytical Processing....Pages 298-311 Skyline View: Efficient Distributed Subspace Skyline Computation....Pages 312-324 HDB-Subdue: A Scalable Approach to Graph Mining....Pages 325-338 Mining Violations to Relax Relational Database Constraints....Pages 339-353 Arguing from Experience to Classifying Noisy Data....Pages 354-365 Dynamic Clustering-Based Estimation of Missing Values in Mixed Type Data....Pages 366-377 The PDG-Mixture Model for Clustering....Pages 378-389 Clustering for Video Retrieval....Pages 390-401 Trends Analysis of Topics Based on Temporal Segmentation....Pages 402-414 Finding N-Most Prevalent Colocated Event Sets....Pages 415-427 Rule Learning with Probabilistic Smoothing....Pages 428-440 Missing Values: Proposition of a Typology and Characterization with an Association Rule-Based Model....Pages 441-452 Recommending Multidimensional Queries....Pages 453-466 Preference-Based Recommendations for OLAP Analysis....Pages 467-478 Back Matter....Pages - Data warehousing and knowledge discovery are increasingly becoming mission-critical technologies for most organizations, both commercial and public, as it becomes incre- ingly important to derive important knowledge from both internal and external data sources. With the ever growing amount and complexity of the data and information available for decision making, the process of data integration, analysis, and knowledge discovery continues to meet new challenges, leading to a wealth of new and exciting research challenges within the area. Over the last decade, the International Conference on Data Warehousing and Knowledge Discovery (DaWaK) has established itself as one of the most important international scientific events within data warehousing and knowledge discovery. DaWaK brings together a wide range of researchers and practitioners working on these topics. The DaWaK conference series thus serves as a leading forum for discu- ing novel research results and experiences within data warehousing and knowledge th discovery. This year's conference, the 11 International Conference on Data Wa- housing and Knowledge Discovery (DaWaK 2009), continued the tradition by d- seminating and discussing innovative models, methods, algorithms, and solutions to the challenges faced by data warehousing and knowledge discovery technologies. This book constitutes the refereed proceedings of the 15th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2013 held in Prague, Czech Republic, in August 2013. The 24 revised full papers and 8 short papers presented were carefully reviewed and selected from 89 submissions. The papers are organized in topical sections on modeling and ETL, query optimization and parallelism, spatial data warehouses and applications, text mining and OLAP, recommendation and prediction, data mining optimization and machine learning techniques, mining and processing data streams, clustering and data mining applications, social network and graph mining, and event sequence and Web mining.