From: Michael Spano
Date: Thu, 11 Oct 2001 16:01:00 -0400
Subject: New Book: Data Mining For Association Rules and Sequential Patterns, by Adamo
Data Mining For Association Rules and Sequential Patterns Sequential and Parallel Algorithms Jean-Marc Adamo, Université de Lyon, France For more information please visit www.springer-ny.com/detail.tpl?isbn=0387950486 This volume describes key algorithms used in the sophisticated data mining of large scale databases. It presents a collection of algorithms based on the lattice structure of the search space; all algorithms are built as processes running on this structure. Given the computational complexity and time requirements of mining for association rules and sequential patterns, the design of efficient algorithms is critical. Most algorithms provided here are designed for both sequential and parallel execution. In addition to enumerative algorithms, the book presents algorithms related to quantitative rule optimization. The algorithms are described in a C-like pseudo-programming language and are supported by detailed computations. Topics and features: * Offers a unified presentation of the main topics relating to association rule mining and sequential pattern mining * Reviews all important algorithms proposed in the literature and presents new algorithms * Utilizes mathematics for accurate algorithm development * Provides solutions to the problem of parallel mining for association rules and sequential patterns * Presents search-space and database partitioning techniques for parallel rule and sequential pattern mining. Practitioners and professionals in information science, computer science, database design, and software engineering will find the work an essential resource, as will teachers, students, and researchers involved in the domains of knowledge discovery, data mining, and data management. 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 2001/272 PP./HARDCOVER/$54.95/ISBN 0-387-95048-6
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