Data Mining on Multimedia Data

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

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

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

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