Data Mining for Association Rules and Sequential Patterns

Sequential and Parallel Algorithms

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Last edited by ImportBot
February 28, 2023 | History

Data Mining for Association Rules and Sequential Patterns

Sequential and Parallel Algorithms

  • 0 Ratings
  • 12 Want to read
  • 0 Currently reading
  • 0 Have read

The book 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. Mining for association rules and sequential patterns is known to be a problem with large computational complexity. The issue of designing efficient parallel algorithms should be considered as critical. Most algorithms in the book are devised for both sequential and parallel execution. Parallel algorithm design takes advantage of the lattice structure of the search space. Partitioning is performed via lattice recursive bisection. Database partitioning is also used as an additional source of parallelism. Part of the motivation for writing this book was postgraduate teaching. 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.

Publish Date
Language
English
Pages
254

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Previews available in: English

Edition Availability
Cover of: Data Mining for Association Rules and Sequential Patterns
Data Mining for Association Rules and Sequential Patterns: Sequential and Parallel Algorithms
2001, Springer New York, Springer
electronic resource : in English
Cover of: Data Mining for Association Rules and Sequential Patterns

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Book Details


Table of Contents

Introduction
Search Space Partition-Based Rule Mining
Apriori and Other Algorithms
Mining for Rules Over Attribute Taxonomies
Constraint-Based Rule Mining
Data Partition-Based Rule Mining
Mining Rules with Categorical and Metric Attributes
Optimizing Rules with Quantitative Attributes
Beyond Support-Confidence Framework
Sequential Patterns: Search Space Partition-Based Mining
Appendix
References
Index.

Edition Notes

Online full text is restricted to subscribers.

Also available in print.

Mode of access: World Wide Web.

Published in
New York, NY

Classifications

Dewey Decimal Class
005.74
Library of Congress
QA76.9.D3, QA75.5-76.95

The Physical Object

Format
[electronic resource] :
Pagination
1 online resource (x, 254p. 54 illus.)
Number of pages
254

ID Numbers

Open Library
OL27029396M
Internet Archive
dataminingforass00adam
ISBN 10
1461265118, 1461300851
ISBN 13
9781461265115, 9781461300854
OCLC/WorldCat
852790268

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History

Download catalog record: RDF / JSON / OPDS | Wikipedia citation
February 28, 2023 Edited by ImportBot import existing book
October 5, 2021 Edited by ImportBot import existing book
October 5, 2021 Edited by ImportBot import existing book
February 15, 2020 Edited by Drini merge authors
June 29, 2019 Created by MARC Bot Imported from Internet Archive item record.