Data Mining on Multimedia Data

Petra Perner

142 pages, parution le 09/04/2003

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Résumé

Despite being a young field of research and development, data mining has proved to be a successful approach to extracting knowledge from huge collections of structured digital data collection as usually stored in databases. Whereas data mining was done in early days primarily on numerical data, nowadays multimedia and Internet applications drive the need to develop data mining methods and techniques that can work on all kinds of data such as documents, images, and signals.

This book introduces the basic concepts of mining multimedia data and demonstrates how to apply these methods in various application fields. It is written for students, ambitioned professionals from industry and medicine, and for scientists who want to contribute R&D work to the field or apply this new technology.

Contents

Introduction

What Is Data Mining?
Some More Real-World Applications
Data Mining Methods - An Overview
Data Mining Viewed from the Data Side
Types of Data
Conclusion

Data Preparation

Data Cleaning
Handling Outlier
Handling Noisy Data
Missing Values Handling
Coding
Recognition of Correlated or Redundant Attributes
Abstraction
Conclusions

Methods for Data Mining

Decision Tree Induction
Case-Based Reasoning
Clustering
Conceptual Clustering
Evaluation of the Model
Feature Subset Selection

Applications

Controlling the Parameters of an Algorithm/Model by Case-Based
Reasoning
Mining Images
Conclusion

Appendix
References
Index

L'auteur - Petra Perner

Institute of Computer Vision and Applied Computer, Leipzig, Germany

Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Petra Perner
Parution	09/04/2003
Nb. de pages	142
Format	15,5 x 23,5
Couverture	Broché
Poids	222g
Intérieur	Noir et Blanc
EAN13	9783540003175