Skip to main content
SpringerLink
Log in
SpringerLink
Log in

Data Mining for Association Rules and Sequential Patterns

Sequential and Parallel Algorithms

  • Book
  • © 2001

Overview

Authors:
  1. Jean-Marc Adamo

    1. Université de Lyon, Villeurbanne, cedex, France

    View author publications

    You can also search for this author in PubMed   Google Scholar

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

Access this book

Log in via an institution
eBook USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (10 chapters)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Introduction

    • Jean-Marc Adamo
    Pages 1-4

  3. Search Space Partition-Based Rule Mining

    • Jean-Marc Adamo
    Pages 5-32

  4. Apriori and Other Algorithms

    • Jean-Marc Adamo
    Pages 33-48

  5. Mining for Rules over Attribute Taxonomies

    • Jean-Marc Adamo
    Pages 49-65

  6. Constraint-Based Rule Mining

    • Jean-Marc Adamo
    Pages 67-78

  7. Data Partition-Based Rule Mining

    • Jean-Marc Adamo
    Pages 79-91

  8. Mining for Rules with Categorical and Metric Attributes

    • Jean-Marc Adamo
    Pages 93-109

  9. Optimizing Rules with Quantitative Attributes

    • Jean-Marc Adamo
    Pages 111-150

  10. Beyond Support-Confidence Framework

    • Jean-Marc Adamo
    Pages 151-184

  11. Search Space Partition-Based Sequential Pattern Mining

    • Jean-Marc Adamo
    Pages 185-228

  12. Back Matter

    Pages 229-254
    Download chapter PDF
Back to top

Keywords

About this book

Data mining includes a wide range of activities such as classification, clustering, similarity analysis, summarization, association rule and sequential pattern discovery, and so forth. The book focuses on the last two previously listed activities. It provides a unified presentation of algorithms for association rule and sequential pattern discovery. For both mining problems, the presentation relies on the lattice structure of the search space. All algorithms are built as processes running on this structure. Proving their properties takes advantage of the mathematical properties of the structure. Part of the motivation for writing this book was postgraduate teaching. One of the main intentions was to make the book a suitable support for the clear exposition of problems and algorithms as well as a sound base for further discussion and investigation. Since the book only assumes elementary mathematical knowledge in the domains of lattices, combinatorial optimization, probability calculus, and statistics, it is fit for use by undergraduate students as well. The algorithms are described in a C-like pseudo programming language. The computations are shown in great detail. This makes the book also fit for use by implementers: computer scientists in many domains as well as industry engineers.

Authors and Affiliations

  • Université de Lyon, Villeurbanne, cedex, France

    Jean-Marc Adamo

Bibliographic Information

  • Book Title: Data Mining for Association Rules and Sequential Patterns

  • Book Subtitle: Sequential and Parallel Algorithms

  • Authors: Jean-Marc Adamo

  • DOI: https://doi.org/10.1007/978-1-4613-0085-4

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Science+Business Media New York 2001

  • Hardcover ISBN: 978-0-387-95048-8Published: 28 December 2000

  • Softcover ISBN: 978-1-4612-6511-5Published: 14 September 2012

  • eBook ISBN: 978-1-4613-0085-4Published: 06 December 2012

  • Edition Number: 1

  • Number of Pages: X, 254

  • Topics: Database Management, Information Storage and Retrieval, Artificial Intelligence, Algorithm Analysis and Problem Complexity

Publish with us

Policies and ethics

Back to top

Search

Navigation