Foundations and Advances in Data Mining: Studies in Fuzziness and Soft Computing, cartea 180
Editat de Wesley Chu, Tsau Young Linen Limba Engleză Paperback – 16 noi 2014
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Springer Berlin, Heidelberg – 15 sep 2005 | 976.02 lei 6-8 săpt. |
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Specificații
ISBN-13: 9783642425387
ISBN-10: 3642425380
Pagini: 352
Ilustrații: X, 342 p.
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.49 kg
Ediția:2005
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Fuzziness and Soft Computing
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3642425380
Pagini: 352
Ilustrații: X, 342 p.
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.49 kg
Ediția:2005
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Fuzziness and Soft Computing
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
The Mathematics of Learning.- Logical Regression Analysis: From Mathematical Formulas to Linguistic Rules.- A Feature/Attribute Theory for Association Mining and Constructing the Complete Feature Set.- A New Theoretical Framework for K-means-type Clustering.- Clustering via Decision Tree Construction.- Incremental Mining on Association Rules.- Mining Association Rules from Tabular Data Guided by Maximal Frequent Itemsets.- Sequential Pattern Mining by Pattern-Growth: Principles and Extensions.- Web Page Classification.- Web Mining – Concepts, Applications, and Research Directions.- Privacy-Preserving Data Mining.
Textul de pe ultima copertă
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.
Caracteristici
Brings together well respected data mining theoreticians and researchers with practical data mining experiences Presents a theoretical foundation Presents important new directions for data-mining research Includes supplementary material: sn.pub/extras