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

Special Issue on Advances in Data Warehousing and Knowledge Discovery

  • Book
  • © 2013

Overview

Editors:
  1. Abdelkader Hameurlain

    1. IRIT, Paul Sabatier University,, Toulouse Cedex, France

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  2. Josef Küng

    1. Institute for Application Oriented Knowledge Processing, Linz, Austria

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  3. Roland Wagner

    1. FAW, University of Linz, Linz, Austria

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  4. Alfredo Cuzzocrea

    1. ICAR-CNR, University of Calabria, Rende (CS), Italy

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  5. Umeshwar Dayal

    1. Hewlett-Packard Laboratories, Palo Alto, USA

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  • Contains the best papers selected from DaWaK 2011
  • Offers an innovative, modern research perspective on data warehousing and knowledge discovery
  • Aims to fulfill innovative requirements posed by the realization of data warehousing and knowledge discovery in emerging fields

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 7790)

Part of the book sub series: Transactions on Large-Scale Data- and Knowledge-Centered Systems (TLDKS)

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Table of contents (8 chapters)

  1. Front Matter

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  2. ETLMR: A Highly Scalable Dimensional ETL Framework Based on MapReduce

    • Xiufeng Liu, Christian Thomsen, Torben Bach Pedersen
    Pages 1-31

  3. The Planning OLAP Model – A Multidimensional Model with Planning Support

    • Bernhard Jaecksch, Wolfgang Lehner
    Pages 32-52

  4. Query Optimization for the NOX OLAP Algebra

    • Ahmad Taleb, Todd Eavis, Hiba Tabbara
    Pages 53-88

  5. Finding Critical Thresholds for Defining Bursts in Event Logs

    • Bibudh Lahiri, Ioannis Akrotirianakis, Fabian Moerchen
    Pages 89-112

  6. Concurrent Semi-supervised Learning with Active Learning of Data Streams

    • Hai-Long Nguyen, Wee-Keong Ng, Yew-Kwong Woon
    Pages 113-136

  7. Efficient Single Pass Ordered Incremental Pattern Mining

    • Yun Sing Koh, Gillian Dobbie
    Pages 137-156

  8. Finding Interesting Rare Association Rules Using Rare Pattern Tree

    • Sidney Tsang, Yun Sing Koh, Gillian Dobbie
    Pages 157-173

  9. Discovering Frequent Patterns from Uncertain Data Streams with Time-Fading and Landmark Models

    • Carson Kai-Sang Leung, Alfredo Cuzzocrea, Fan Jiang
    Pages 174-196

  10. Back Matter

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Keywords

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, the eighth issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains eight revised selected regular papers focusing on the following topics: scalable data warehousing via MapReduce, extended OLAP multidimensional models, naive OLAP engines and their optimization, advanced data stream processing and mining, semi-supervised learning of data streams, incremental pattern mining over data streams, association rule mining over data streams, frequent pattern discovery over data streams.

Editors and Affiliations

  • IRIT, Paul Sabatier University,, Toulouse Cedex, France

    Abdelkader Hameurlain

  • Institute for Application Oriented Knowledge Processing, Linz, Austria

    Josef Küng

  • FAW, University of Linz, Linz, Austria

    Roland Wagner

  • ICAR-CNR, University of Calabria, Rende (CS), Italy

    Alfredo Cuzzocrea

  • Hewlett-Packard Laboratories, Palo Alto, USA

    Umeshwar Dayal

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