Logo - springer
Slogan - springer

Computer Science - Database Management & Information Retrieval | Transactions on Large-Scale Data- and Knowledge-Centered Systems VIII - Special Issue on Advances

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

Special Issue on Advances in Data Warehousing and Knowledge Discovery

Hameurlain, A., Küng, J., Wagner, R., Cuzzocrea, A., Dayal, U. (Eds.)

2013, XII, 197 p. 99 illus.

Available Formats:
eBook
Information

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.

 
$69.99

(net) price for USA

ISBN 978-3-642-37574-3

digitally watermarked, no DRM

Included Format: PDF

download immediately after purchase


learn more about Springer eBooks

add to marked items

Softcover
Information

Softcover (also known as softback) version.

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.

 
$95.00

(net) price for USA

ISBN 978-3-642-37573-6

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days


add to marked items

  • 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
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.

Content Level » Research

Keywords » ETL - data mining - event logs - frequent patterns - query optimization

Related subjects » Database Management & Information Retrieval - Information Systems and Applications

Table of contents 

ETLMR: A Highly Scalable Dimensional ETL Framework Based on MapReduce.- The Planning OLAP Model – A Multidimensional Model with Planning Support.- Query Optimization for the NOX OLAP Algebra.- Finding Critical Thresholds for Defining Bursts in Event Logs.- Concurrent Semi-supervised Learning with Active Learning of Data Streams.- Efficient Single Pass Ordered Incremental Pattern Mining.- Finding Interesting Rare Association Rules Using Rare Pattern Tree.- Discovering Frequent Patterns from Uncertain Data Streams with Time-Fading and Landmark Models.

Popular Content within this publication 

 

Articles

Read this Book on Springerlink

Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Data Mining and Knowledge Discovery.