Name: Multimedia Data Mining: A Systematic Introduction to Concepts and Theory (en Inglés)
Price: 132900.00 CLP
Availability: InStock
Author: Zhang, Zhongfei ; Zhang, Ruofei
ISBN: 9781584889663

portada Multimedia Data Mining: A Systematic Introduction to Concepts and Theory (en Inglés)

Formato

Libro Físico

Autor

Zhongfei Zhang

Ruofei Zhang

Editorial

CRC Press

Idioma

Inglés

N° páginas

320

Encuadernación

Tapa Dura

Dimensiones

23.6 x 15.5 x 2.3 cm

Peso

0.57 kg.

ISBN

1584889667

ISBN13

9781584889663

Categorías

Aplicaciones gráficas y multimedia
Data mining: minería de datos

Multimedia Data Mining: A Systematic Introduction to Concepts and Theory (en Inglés)

Zhongfei Zhang (Autor) · Ruofei Zhang (Autor) · CRC Press · Tapa Dura

Libro Físico

$ 132.900

$ 241.630

Ahorras: $ 108.730

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Reseña del libro "Multimedia Data Mining: A Systematic Introduction to Concepts and Theory (en Inglés)"

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.