Multimedia Data Mining : A Systematic Introduction to Concepts and Theory

This novel, self-contained book introduces the most current, state-of-the-art multimedia data mining concepts and theory. It reviews the theoretical foundations of the subject, including feature extraction and representations, knowledge representations, statistical learning theory, and soft computing theory. Clarifying perplexing topics scattered throughout research papers in the field, the book explores the relationship of multimedia data mining to other related areas, such as artificial intelligence. It also highlights various applications that illustrate how multimedia data mining can solve many real-world problems, such as image annotation, video search, and audio classification.

Collecting the latest developments in the field, Multimedia Data Mining: A Systematic Introduction to Concepts and Theory defines multimedia data mining, its theory, and its applications. Two of the most active researchers in multimedia data mining explore how this young area has rapidly developed in recent years.

The book first discusses the theoretical foundations of multimedia data mining, presenting commonly used feature representation, knowledge representation, statistical learning, and soft computing techniques. It then provides application examples that showcase the great potential of multimedia data mining technologies. In this part, the authors show how to develop a semantic repository training method and a concept discovery method in an imagery database. They demonstrate how knowledge discovery helps achieve the goal of imagery annotation. The authors also describe an effective solution to large-scale video search, along with an application of audio data classification and categorization.

This novel, self-contained book examines how the merging of multimedia and data mining research can promote the understanding and advance the development of knowledge discovery in multimedia data.