Ebook: Data Mining: Theory, Methodology, Techniques, and Applications
- Genre: Computers
- Tags: Artificial Intelligence (incl. Robotics), Computation by Abstract Devices, Information Storage and Retrieval, Database Management, Pattern Recognition
- Series: Lecture Notes in Computer Science 3755 : Lecture Notes in Artificial Intelligence
- Year: 2006
- Publisher: Springer-Verlag Berlin Heidelberg
- Edition: 1
- Language: English
- pdf
This volume provides a snapshot of the current state of the art in data mining, presenting it both in terms of technical developments and industrial applications. The collection of chapters is based on works presented at the Australasian Data Mining conferences and industrial forums.
Authors include some of Australia's leading researchers and practitioners in data mining. The volume also contains chapters by regional and international authors. The original papers were initially reviewed for workshops, conferences and forums.
The 25 articles in this state-of-the-art survey were carefully reviewed and selected from numerous contributions during at least two rounds of reviewing and improvement for inclusion in the book. They provide an interesting and broad update on current research and development in data mining.
The book is divided into two parts. It starts with state-of-the-art research papers organized in topical sections on methodological advances, data linkage, text mining, and temporal and sequence mining. The second part comprises papers on state-of-the-art industrial applications from the fields of health, finance and retail.
This volume provides a snapshot of the current state of the art in data mining, presenting it both in terms of technical developments and industrial applications. The collection of chapters is based on works presented at the Australasian Data Mining conferences and industrial forums. Authors include some of Australia's leading researchers and practitioners in data mining. The volume also contains chapters by regional and international authors. The original papers were initially reviewed for the workshops, conferences and forums.
The 25 articles in this state-of-the-art survey were carefully reviewed and selected from numerous contributions during at least two rounds of reviewing and improvement for inclusion in the book. They provide an interesting and broad update on current research and development in data mining. The book is divided into two parts. It starts with state-of-the-art research papers organized in topical sections on methodological advances, data linkage, text mining, and temporal and sequence mining. The second part comprises papers on state-of-the-art industrial applications from the fields of health, finance and retail.