Skip to main content
SpringerLink
Log in
Book cover
  • Conference proceedings
  • © 2000

Large-Scale Parallel Data Mining

Editors:

  1. Mohammed J. Zaki

    1. Computer Science Department, Rensselaer Polytechnic Institute, Troy, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Ching-Tien Ho

    1. K55/B1, IBM Almaden Research Center, San Jose, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 1759)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Sections

Buy it now

eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

This is a preview of subscription content, log in via an institution to check for access.

Table of contents (13 papers)

  1. Front Matter

    Pages I-VIII
    PDF

  2. Large-Scale Parallel Data Mining

  3. Mining Frameworks

    1. The Integrated Delivery of Large-Scale Data Mining: The ACSys Data Mining Project

      • Graham Williams, Irfan Altas, Sergey Bakin, Peter Christen, Markus Hegland, Alonso Marquez et al.
      Pages 24-54

    2. A High Performance Implementation of the Data Space Transfer Protocol (DSTP)

      • Stuart Bailey, Emory Creel, Robert Grossman, Srinath Gutti, Harinath Sivakumar
      Pages 55-64

    3. Active Mining in a Distributed Setting

      • Srinivasan Parthasarathy, Sandhya Dwarkadas, Mitsunori Ogihara
      Pages 65-82

  4. Associations and Sequences

    1. Efficient Parallel Algorithms for Mining Associations

      • Mahesh V. Joshi, Eui-Hong Sam Han, George Karypis, Vipin Kumar
      Pages 83-126

    2. Parallel Branch-and-Bound Graph Search for Correlated Association Rules

      • Shinichi Morishita, Akihiro Nakaya
      Pages 127-144

    3. Parallel Generalized Association Rule Mining on Large Scale PC Cluster

      • Takahiko Shintani, Masaru Kitsuregawa
      Pages 145-160

  5. Classification

    1. Parallel Predictor Generation

      • D. B. Skillicorn
      Pages 190-196

    2. Efficient Parallel Classification Using Dimensional Aggregates

      • Sanjay Goil, Alok Choudhary
      Pages 197-210

    3. Learning Rules from Distributed Data

      • Lawrence O. Hall, Nitesh Chawla, Kevin W. Bowyer, W. Philip Kegelmeyer
      Pages 211-220

  6. Clustering

    1. Collective, Hierarchical Clustering from Distributed, Heterogeneous Data

      • Erik L. Johnson, Hillol Kargupta
      Pages 221-244

    2. A Data-Clustering Algorithm on Distributed Memory Multiprocessors

      • Inderjit S. Dhillon, Dharmendra S. Modha
      Pages 245-260

  7. Back Matter

    Pages 261-261
    PDF
Back to top

Keywords

Back to top

Editors and Affiliations

  • Computer Science Department, Rensselaer Polytechnic Institute, Troy, USA

    Mohammed J. Zaki

  • K55/B1, IBM Almaden Research Center, San Jose, USA

    Ching-Tien Ho

Back to top

Bibliographic Information

Back to top

Publish with us

Policies and ethics

Back to top
Access via your institution

Buy it now

eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Search

Navigation