Design and Implementation of Data Mining Tools Front Cover

Design and Implementation of Data Mining Tools

  • Length: 272 pages
  • Edition: 1
  • Publisher:
  • Publication Date: 2009-06-18
  • ISBN-10: 1420045903
  • ISBN-13: 9781420045901
  • Sales Rank: #14886073 (See Top 100 Books)

Focusing on three applications of data mining, Design and Implementation of Data Mining Tools explains how to create and employ systems and tools for intrusion detection, Web page surfing prediction, and image classification. Mainly based on the authors’ own research work, the book takes a practical approach to the subject.

The first part of the book reviews data mining techniques, such as artificial neural networks and support vector machines, as well as data mining applications. The second section covers the design and implementation of data mining tools for intrusion detection. It examines various designs and performance results, along with the strengths and weaknesses of the approaches. The third part presents techniques to solve the WWW prediction problem. The final part describes models that the authors have developed for image classification.

Showing step by step how data mining tools are developed, this hands-on guide discusses the performance results, limitations, and unique contributions of data mining systems. It provides essential information for technologists to decide on the tools to select for a particular application, for developers to focus on alternative designs if an approach is unsuitable, and for managers to choose whether to proceed with a data mining project.

Table of Contents

Chapter 1 Introduction

Part I Data Mining Techniques And Applications
Chapter 2 Data Mining Techniques
Chapter 3 Data Mining Applications

Part II Data Mining Tool For Intrusion Detection
Chapter 4 Data Mining For Security Applications
Chapter 5 Dynamic Growing Self-Organizing Tree Algorithm
Chapter 6 Data Reduction Using Hierarchical Clustering And Rocchio Bundling
Chapter 7 Intrusion Detection Results

Part III Data Mining Tool For Web Page Surfing Prediction
Chapter 8 Web Data Management And Mining
Chapter 9 Effective Web Page Prediction Using Hybrid Model
Chapter 10 Multiple Evidence Combination For Www Prediction
Chapter 11 Www Prediction Results

Part IV Data Mining Tool For Image Classification
Chapter 13 Image Classifcation Models
Chapter 14 Subspace Clustering And Automatic Image Annotation
Chapter 15 Enhanced Weighted Feature Selection
Chapter 16 Image Classifcation And Performance Analysis
Chapter 17 Summary And Directions

Appendix A Data Management Systems: Developments And Trends

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