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

12th International Conference, DaWaK 2010, Bilbao, Spain, August 30 - September 2, 2010, Proceedings

  • Conference proceedings
  • © 2010

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Editors:
  1. Torben Bach Pedersen

    1. Department of Computer Science, Aalborg University, Aalborg, Denmark

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    You can also search for this editor in PubMed   Google Scholar

  2. Mukesh K. Mohania

    1. IBM India Research Lab, 4, Block C, Institutional Area, New Delhi, India

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    You can also search for this editor in PubMed   Google Scholar

  3. A Min Tjoa

    1. Institute of Software Technology, Vienna University of Technology, Vienna, Austria

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 6263)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Included in the following conference series:

Conference proceedings info: DaWaK 2010.

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About this book

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.

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Table of contents (26 papers)

  1. Front Matter

    Download chapter PDF

  2. Data Warehouse Modeling and Spatial Data Warehouses

    1. Logic Programming for Data Warehouse Conceptual Schema Validation

      • Carlo dell’Aquila, Francesco Di Tria, Ezio Lefons, Filippo Tangorra
      Pages 1-12

    2. A Model-Driven Heuristic Approach for Detecting Multidimensional Facts in Relational Data Sources

      • Andrea Carmè, Jose-Norberto Mazón, Stefano Rizzi
      Pages 13-24

    3. Physical Design and Implementation of Spatial Data Warehouses Supporting Continuous Fields

      • Leticia Gómez, Alejandro Vaisman, Esteban Zimányi
      Pages 25-39

    4. Benchmarking Spatial Data Warehouses

      • Thiago Luís Lopes Siqueira, Ricardo Rodrigues Ciferri, Valéria Cesário Times, Cristina Dutra de Aguiar Ciferri
      Pages 40-51

  3. Mining Social Networks and Graphs

    1. Discovering Community-Oriented Roles of Nodes in a Social Network

      • Bin-Hui Chou, Einoshin Suzuki
      Pages 52-64

    2. A Graph-Based Clustering Scheme for Identifying Related Tags in Folksonomies

      • Symeon Papadopoulos, Yiannis Kompatsiaris, Athena Vakali
      Pages 65-76

    3. Frequent Sub-graph Mining on Edge Weighted Graphs

      • Chuntao Jiang, Frans Coenen, Michele Zito
      Pages 77-88

  4. Physical Data Warehouse Design

    1. \(\mathcal{F}\)&\(\mathcal{A}\): A Methodology for Effectively and Efficiently Designing Parallel Relational Data Warehouses on Heterogenous Database Clusters

      • Ladjel Bellatreche, Alfredo Cuzzocrea, Soumia Benkrid
      Pages 89-104

    2. Yet Another Algorithms for Selecting Bitmap Join Indexes

      • Ladjel Bellatreche, Kamel Boukhalfa
      Pages 105-116

    3. Speeding Up Queries in Column Stores

      • Christian Lemke, Kai-Uwe Sattler, Franz Faerber, Alexander Zeier
      Pages 117-129

  5. Dependency Mining

    1. Mining Non-redundant Information-Theoretic Dependencies between Itemsets

      • Michael Mampaey
      Pages 130-141

    2. Discovery and Application of Functional Dependencies in Conjunctive Query Mining

      • Bart Goethals, Dominique Laurent, Wim Le Page
      Pages 142-156

    3. Using Transitivity to Increase the Accuracy of Sample-Based Pearson Correlation Coefficients

      • Taylor Phillips, Chris GauthierDickey, Ramki Thurimella
      Pages 157-171

  6. Business Intelligence and Analytics

    1. The NOX Framework: Native Language Queries for Business Intelligence Applications

      • Todd Eavis, Hiba Tabbara, Ahmad Taleb
      Pages 172-189

    2. Experience in Extending Query Engine for Continuous Analytics

      • Qiming Chen, Meichun Hsu
      Pages 190-202

    3. 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
      Pages 203-214

  7. Outlier and Image Mining

    1. A Fast Randomized Method for Local Density-Based Outlier Detection in High Dimensional Data

      • Minh Quoc Nguyen, Edward Omiecinski, Leo Mark, Danesh Irani
      Pages 215-226

    2. Specialty Mining

      • Hanuma Kumar, Rohit Paravastu, Vikram Pudi
      Pages 227-238

    3. Region of Interest Based Image Categorization

      • Ashraf Elsayed, Frans Coenen, Marta García-Fiñana, Vanessa Sluming
      Pages 239-250
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Other volumes

  1. Data Warehousing and Knowledge Discovery

Editors and Affiliations

  • Department of Computer Science, Aalborg University, Aalborg, Denmark

    Torben Bach Pedersen

  • IBM India Research Lab, 4, Block C, Institutional Area, New Delhi, India

    Mukesh K. Mohania

  • Institute of Software Technology, Vienna University of Technology, Vienna, Austria

    A Min Tjoa

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