Foundations And Advances in Data Mining. Questo articolo non è disponibile.
Lingua: inglese
Editore: Springer, 2005
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Codice articolo 3496776
- Titolo
- Foundations And Advances in Data Mining
- Autore
- Chu, Wesley (EDT); Lin, Tsau Young (EDT)
- Editore
- Springer
- Anno di pubblicazione
- 2005
- Condizione
- As New
- Rilegatura
- Rilegato
- Lingua
- inglese
- ISBN 10
- 3540250573
- ISBN 13
- 9783540250579
With the growing use of information technology and the recent advances in web systems, the amount of data available to users has increased exponentially. Thus, there is a critical need to understand the content of the data. As a result, data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this carefully edited volume a theoretical foundation as well as important new directions for data-mining research are presented. It brings together a set of well respected data mining theoreticians and researchers with practical data mining experiences. The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.
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Dalla quarta di copertina
With the growing use of information technology and the recent advances in web systems, the amount of data available to users has increased exponentially. Thus, there is a critical need to understand the content of the data. As a result, data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this carefully edited volume a theoretical foundation as well as important new directions for data-mining research are presented. It brings together a set of well respected data mining theoreticians and researchers with practical data mining experiences. The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.
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