Data Warehousing and Knowledge Discovery: 12th International Conference, DaWaK 2010, Bilbao, Spain, August 30 - September 2, 2010, Proceedings

by Mukesh K. Mohania (Editor), A Min Tjoa (Editor)

Overview

Data warehousing and knowledge discovery has been widely accepted as a key te- nology 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 considered become more and more complex in both structure and semantics. New developments such as cloud computing add to the challenges with massive scaling, a new computing infrastructure, and new types of data. Consequently, the process of retrieval and knowledge discovery from this huge amount of heterogeneous complex data forms the litmus test for research in the area. In the last decade, the International Conference on Data Warehousing and Kno- edge Discovery (DaWaK) has become one of the most important international sci- tific events bringing together researchers, developers, and practitioners to discuss the latest research issues and experiences in developing and deploying data warehousing and knowledge discovery systems, applications, and solutions. th This year’s conference, the 12 International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2010), continued the tradition by discussing and disseminating innovative principles, methods, algorithms, and solutions to challe- ing problems faced in the development of data warehousing, knowledge discovery, the emerging area of "cloud intelligence," and applications within these areas. In order to better reflect novel trends and the diversity of topics, the conference was organized in four tracks: Cloud Intelligence, Data Warehousing, Knowledge Discovery, and Industry and Applications.

Product Details

ISBN-13:	9783642151040
Publisher:	Springer Berlin Heidelberg
Publication date:	12/01/2010
Series:	Lecture Notes in Computer Science , #6263
Edition description:	2010
Pages:	338
Product dimensions:	6.20(w) x 9.30(h) x 0.80(d)

Table of Contents

Data Warehouse Modeling and Spatial Data Warehouses

Logic Programming for Data Warehouse Conceptual Schema Validation Carlo dell'Aquila Francesco Di Tria Ezio Lefons Filippo Tangorra 1

A Model-Driven Heuristic Approach for Detecting Multidimensional Facts in Relational Data Sources Andrea Carmè Jose-Norberto Mazón Stefano Rizzi 13

Physical Design and Implementation of Spatial Data Warehouses Supporting Continuous Fields Leticia Gómez Alejandro Vaisman Esteban Zimányi 25

Benchmarking Spatial Data Warehouses Thiago Luís Lopes Siqueira Ricardo Rodrigues Ciferri Valéria Cesário Times Cristina Dutra de Aguiar Ciferri 40

Mining Social Networks and Graphs

Discovering Community-Oriented Roles of Nodes in a Social Network Bin-Hui Chou Einoshin Suzuki 52

A Graph-Based Clustering Scheme for Identifying Related Tags in Folksonomies Symeon Papadopoulos Yiannis Kompatsiaris Athena Vakali 65

Frequent Sub-graph Mining on Edge Weighted Graphs Chuntao Jiang Frans Coenen Michele Zito 77

Physical Data Warehouse Design

F&A: A Methodology for Effectively and Efficiently Designing Parallel Relational Data Warehouses on Heterogenous Database Clusters Ladjel Bellatreche Alfredo Cuzzocrea Soumia Benkrid 89

Yet Another Algorithms for Selecting Bitmap Join Indexes Ladjel Bellatreche Kamel Boukhalfa 105

Speeding Up Queries in Column Stores: A Case for Compression Christian Lemke Kai-Uwe Sattler Franz Faerber Alexander Zeier 117

Dependency Mining

Mining Non-redundant Information-Theoretic Dependencies between Itemsets Michael Mampaey 130

Discovery and Application of Functional Dependencies in Conjunctive Query Mining Bart Goethals Dominique Laurent Wim Le Page 142

Using Transitivity to Increase the Accuracy of Sample-Based Pearson Correlation Coefficients Taylor Phillips Chris GauthierDickey Ramki Thurimella 157

Business Intelligence and Analytics

The NOX Framework: Native Language Queries for Business Intelligence Applications Todd Eavis Hiba Tabbara Ahmad Taleb 172

Experience in Extending Query Engine for Continuous Analytics Qiming Chen Meichun Hsu 190

Development of a Business Intelligence Environment for e-Gov Using Open Source Technologies Eduardo Zanoni Marques Rodrigo Sanches Miani Everton Luiz de Almeida Gago Júnior Leonardo de Souza Mendes 203

Outlier and Image Mining

A Fast Randomized Method for Local Density-Based Outlier Detection in High Dimensional Data Minh Quoc Nguyen Edward Omiecinski Leo Mark Danesh Irani 215

Specialty Mining Hanuma Kumar Rohit Paravastu Vikram Pudi 227

Region of Interest Based Image Categorization Ashraf Elsayed Frans Goenen Marta García-Fiñana Vanessa Sluming 239

Pattern Mining

Meta-learning for Post-processing of Association Rules Petr Berka Jan Rauch 251

A Relational Approach for Discovering Frequent Patterns with Disjunctions Corrado Loglisci Michelangelo Ceci Donato Malerba 263

An Occurrence Based Approach to Mine Emerging Sequences Kang Deng Osmar R. Zaïane 275

Mining Closed Itemsets in Data stream Using Formal Concept Analysis Anamika Gupta Vasudha Bhatnagar Naveen Kumar 285

Data Cleaning and Variable Selection

XML Data Fusion Frantchesco Cecchin Cristina Dutra de Aguiar Ciferri Carmem Satie Hara 297

An Efficient Duplicate Record Detection Using q-Grams Array Inverted Index Alfredo Ferro Rosalba Giugno Piera Laura Puglisi Alfredo Pulvirenti 309

Modelling Complex Data by Learning Which Variable to Construct Françoise Fessant Aurélie Le Cam Marc Boullé Raphaël Féraud 324

Author Index 337