Advertisement

Transactions on Large-Scale Data- and Knowledge-Centered Systems XXVI

Special Issue on Data Warehousing and Knowledge Discovery

  • Abdelkader Hameurlain
  • Josef Küng
  • Roland Wagner
  • Ladjel Bellatreche
  • Mukesh Mohania

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9670)

Also part of the Transactions on Large-Scale Data- and Knowledge-Centered Systems book sub series (TLDKS, volume 9670)

Table of contents

  1. Front Matter
    Pages I-XI
  2. Fatimah B. Abdullahi, Frans Coenen, Russell Martin
    Pages 1-31
  3. Nicolas Durand, Mohamed Quafafou
    Pages 32-60
  4. Daniel K. Antwi, Herna L. Viktor
    Pages 61-88
  5. David Korfkamp, Stefan Gudenkauf, Martin Rohde, Eunice Sirri, Joachim Kieschke, Kolja Blohm et al.
    Pages 89-107
  6. Back Matter
    Pages 109-109

About this book

Introduction

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments.

This volume, the 26th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, focuses on Data Warehousing and Knowledge Discovery from Big Data, and contains extended and revised versions of four papers selected as the best papers from the 16th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2014), held in Munich, Germany, during September 1-5, 2014. The papers focus on data cube computation, the construction and analysis of a data warehouse in the context of cancer epidemiology, pattern mining algorithms, and frequent item-set border approximation.

Keywords

data warehouse life cycle data analysis personalization data integration pattern mining frequent itemset border vertical partitioning high dimensionality data big data approximation banded pattern mining cancer epidemiology dualization hypergraph transversals partial materialization real-time OLAP record linkage smart data cubes user interests zero-one data

Editors and affiliations

  • Abdelkader Hameurlain
    • 1
  • Josef Küng
    • 2
  • Roland Wagner
    • 3
  • Ladjel Bellatreche
    • 4
  • Mukesh Mohania
    • 5
  1. 1.IRIT, Paul Sabatier UniversityToulouseFrance
  2. 2.FAW, University of LinzLinzAustria
  3. 3.FAW, University of LinzLinzAustria
  4. 4.LIAS/ISAE-ENSMAChasseneuilFrance
  5. 5.IBM India Research LabNew DelhiIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-49784-5
  • Copyright Information Springer-Verlag Berlin Heidelberg 2016
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-662-49783-8
  • Online ISBN 978-3-662-49784-5
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site