Knowledge Discovery and Data Mining: The Info-Fuzzy Network (IFN) Methodology

✍ Scribed by Oded Maimon, Mark Last (auth.)

Publisher: Springer US
Year: 2001
Tongue: English
Leaves: 169
Series: Massive Computing 1
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall process for Knowledge Discovery in Databases. The accessibility and abundance of information today makes this a topic of particular importance and need. The book has three main parts complemented by appendices as well as software and project data that are accessible from the book's web site (http://www.eng.tau.ac.iV-maimonlifn-kdg£). Part I (Chapters 1-4) starts with the topic of KDD and DM in general and makes reference to other works in the field, especially those related to the information theoretic approach. The remainder of the book presents our work, starting with the IFN theory and algorithms. Part II (Chapters 5-6) discusses the methodology of application and includes case studies. Then in Part III (Chapters 7-9) a comparative study is presented, concluding with some advanced methods and open problems. The IFN, being a generic methodology, applies to a variety of fields, such as manufacturing, finance, health care, medicine, insurance, and human resources. The appendices expand on the relevant theoretical background and present descriptions of sample projects (including detailed results).

✦ Table of Contents

Front Matter....Pages i-xvii
Front Matter....Pages 1-1
Introduction....Pages 3-21
Automated Data Pre-Processing....Pages 23-29
Information-Theoretic Connectionist Networks....Pages 31-51
Post-Processing of Data Mining Results....Pages 53-59
Front Matter....Pages 61-61
Methodology of Application....Pages 63-70
Case Studies....Pages 71-103
Front Matter....Pages 105-105
Comparative Study....Pages 107-121
Advanced data mining methods....Pages 123-133
Summary and Some Open Problems....Pages 135-140
Back Matter....Pages 141-168

✦ Subjects

Data Structures, Cryptology and Information Theory; Artificial Intelligence (incl. Robotics); Coding and Information Theory; Mathematical Logic and Foundations; Statistics, general

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