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

Selected Papers from DaWaK 2012

  • Abdelkader Hameurlain
  • Josef Küng
  • Roland Wagner
  • Alfredo Cuzzocrea
  • Umeshwar Dayal

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9260)

Also part of the Transactions on Large-Scale Data- and Knowledge-Centered Systems book sub series (TLDKS, volume 9260)

Table of contents

  1. Front Matter
    Pages I-XIII
  2. Suan Lee, Jinho Kim, Yang-Sae Moon, Wookey Lee
    Pages 1-19
  3. Ali Hassan, Frank Ravat, Olivier Teste, Ronan Tournier, Gilles Zurfluh
    Pages 20-47
  4. Laurynas Šikšnys, Christian Thomsen, Torben Bach Pedersen
    Pages 48-72
  5. Wiem Abdelbaki, Sadok Ben Yahia, Riadh Ben Messaoud
    Pages 73-93
  6. Alfredo Cuzzocrea, Fan Jiang, Carson K. Leung, Dacheng Liu, Aaron Peddle, Syed K. Tanbeer
    Pages 115-139
  7. David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie
    Pages 140-160
  8. Back Matter
    Pages 185-185

About this book


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 21st 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 eight papers selected as the best papers from the 14th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2012), held in Vienna, Austria, during September 3-6, 2012. These papers cover several advanced Big Data topics, ranging from data cube computation using MapReduce to multiple aggregations over multidimensional databases, from data warehousing systems over complex energy data to OLAP-based prediction models, from extended query engines for continuous stream analytics to popular pattern mining, and from rare pattern mining to enhanced knowledge discovery from large cross-document corpora.


OLAP-based prediction big data cloud data management complex energy data content analysis continuous stream analytics data analytics data cube computation data streams data warehousing information retrieval knowledge discovery link analysis machine learning modular neural networks multidimensional databases pattern mining query optimization query processing smart grids

Editors and affiliations

  • Abdelkader Hameurlain
    • 1
  • Josef Küng
    • 2
  • Roland Wagner
    • 3
  • Alfredo Cuzzocrea
    • 4
  • Umeshwar Dayal
    • 5
  1. 1.IRIT, Paul Sabatier UniversityToulouseFrance
  2. 2.FAW, University of LinzLinzAustria
  3. 3.FAW, University of LinzLinzAustria
  4. 4.ICAR-CNR and University of CalabriaRendeItaly
  5. 5.Hewlett-Packard LabatoriesPalo AltoUSA

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2015
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science Computer Science (R0)
  • Print ISBN 978-3-662-47803-5
  • Online ISBN 978-3-662-47804-2
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
Industry Sectors
Materials & Steel
Chemical Manufacturing
Finance, Business & Banking
IT & Software
Consumer Packaged Goods
Energy, Utilities & Environment