Research and Trends in Data Mining Technologies and Applications, 1st Edition

  • Published By:
  • ISBN-10: 1599042738
  • ISBN-13: 9781599042732
  • Grade Level Range: College Freshman - College Senior
  • 300 Pages | eBook
  • Original Copyright 2007 | Published/Released April 2007
  • This publication's content originally published in print form: 2007

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About

Overview

Activities in data warehousing and mining are constantly emerging. Data mining methods, algorithms, online analytical processes, data mart and practical issues consistently evolve, providing a challenge for professionals in the field. Research and Trends in Data Mining Technologies and Applications focuses on the integration between the fields of data warehousing and data mining, with emphasis on the applicability to real-world problems. This book provides an international perspective, highlighting solutions to some of researchers' toughest challenges. Developments in the knowledge discovery process, data models, structures, and design serve as answers and solutions to these emerging challenges.

Table of Contents

Front Cover.
Title Page.
Copyright Page.
Research and Trends in Data Mining Technologies and Applications: Table of Contents.
Preface.
1: Data Warehousing and Mining.
2: Combining Data Warehousing and Data Mining Techniques for Web Log Analysis.
3: Computing Dense Cubes Embedded in Sparse Data.
4: Exploring Similarities Across High-Dimensional Datasets.
5: Patterns.
6: Pattern Comparison in Data Mining: A Survey.
7: Mining Frequent Patterns Using Self-Organizing Map.
8: An Efficient Compression Technique for Vertical Mining Methods.
9: Data Mining in Bioinformatics.
10: A Tutorial on Hierarchical Classification with Applications in Bioinformatics.
11: Topological Analysis and Sub-Network Mining of Protein-Protein Interactions.
12: Data Mining Techniques.
13: Introduction to Data Mining Techniques via Multiple Criteria Optimization Approaches and Applications.
14: Linguistic Rule Extraction from Support Vector Machine Classifiers.
15: Graph-Based Data Mining.
16: Facilitating and Improving the Use of Web Services with Data Mining.
About the Authors.
Index.